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Keywords:

  • canopy scale;
  • elevated CO2;
  • emission modeling;
  • global climate change;
  • growth modeling;
  • isoprene emission;
  • leaf scale

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  9. Supporting Information
  • Effects of elevated atmospheric [CO2] on plant isoprene emissions are controversial. Relying on leaf-scale measurements, most models simulating isoprene emissions in future higher [CO2] atmospheres suggest reduced emission fluxes. However, combined effects of elevated [CO2] on leaf area growth, net assimilation and isoprene emission rates have rarely been studied on the canopy scale, but stimulation of leaf area growth may largely compensate for possible [CO2] inhibition reported at the leaf scale. This study tests the hypothesis that stimulated leaf area growth leads to increased canopy isoprene emission rates.
  • We studied the dynamics of canopy growth, and net assimilation and isoprene emission rates in hybrid aspen (Populus tremula × Populus tremuloides) grown under 380 and 780 μmol mol−1 [CO2]. A theoretical framework based on the Chapman–Richards function to model canopy growth and numerically compare the growth dynamics among ambient and elevated atmospheric [CO2]-grown plants was developed.
  • Plants grown under elevated [CO2] had higher C : N ratio, and greater total leaf area, and canopy net assimilation and isoprene emission rates. During ontogeny, these key canopy characteristics developed faster and stabilized earlier under elevated [CO2]. However, on a leaf area basis, foliage physiological traits remained in a transient state over the whole experiment.
  • These results demonstrate that canopy-scale dynamics importantly complements the leaf-scale processes, and that isoprene emissions may actually increase under higher [CO2] as a result of enhanced leaf area production.

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 majority of biogenic volatile organic compounds (BVOCs) are emitted from terrestrial sources such as forests, grasslands, shrublands and croplands (Guenther et al., 1995; Peñuelas & Staudt, 2010). Isoprene is among the most abundant BVOCs emitted from vegetation (Sharkey & Yeh, 2001; Sharkey et al., 2008). Its share may reach up to 40% of total BVOC emissions, with estimated yearly totals of 440–660 Tg C yr−1 (Guenther et al., 2006). Previous studies have revealed that isoprene plays an important physiological role in protecting plants from biotic and abiotic stresses (Sharkey & Singsaas, 1995; Behnke et al., 2007; Loivamäki et al., 2008; Vickers et al., 2009; Velikova et al., 2011). In particular, dissipation of excess energy to protect the photosynthetic apparatus (Sanadze, 2010), stabilizing thylakoid membranes at high temperatures (Sharkey & Singsaas, 1995; Singsaas & Sharkey, 1998, 2000; Owen & Peñuelas, 2005; Behnke et al., 2007; Velikova et al., 2011), quenching of reactive oxygen species (Affek & Yakir, 2002; Sharkey et al., 2008; Vickers et al., 2009), and repelling herbivores (Loivamäki et al., 2008) have been reported.

Isoprene also plays a major role in tropospheric photochemistry and contributes to secondary organic aerosol formation, thereby potentially influencing large-scale Earth system processes (Fehsenfeld et al., 1992; Claeys et al., 2004; Hallquist et al., 2009). As a very reactive volatile compound, it strongly affects ozone and secondary organic aerosol formation in the troposphere (Williams et al., 1997; Fuentes et al., 2000; Kroll et al., 2005) and partly controls the lifetime of the glasshouse gas methane by its reaction with hydroxyl radicals (Kaplan et al., 2006).

Isoprene is formed in chloroplasts by isoprene synthase from its immediate precursor dimethylallyldiphosphate (DMADP) via the 1-deoxy-d-xylulose-5-phosphate (DOXP) pathway (Lichtenthaler et al., 1997) and a major part of its carbon skeleton is derived from recently assimilated photosynthates (Lichtenthaler, 1999; Affek & Yakir, 2003; Trowbridge et al., 2012). Thus, DMADP availability and isoprene synthase activity are key factors determining the isoprene emission rate (Calfapietra et al., 2008; Rasulov et al., 2009, 2010; Li et al., 2011), although the physiological regulation mechanisms of isoprene synthesis have still not been fully resolved. The instantaneous isoprene emission rate is strongly light- and temperature-dependent and this response is similar for different plant species. The instantaneous responses result from changes in the supply of intermediates to isoprene synthesis (Loreto & Sharkey, 1993; Schnitzler et al., 2004; Magel et al., 2006; Rasulov et al., 2009, 2010).

Over the long term, prevailing environmental conditions and leaf ontogeny affect the development of isoprene synthesis capacity (Kuzma & Fall, 1993; Sasaki et al., 2005; Loivamäki et al., 2007; Cinege et al., 2009; Niinemets et al., 2010b; Sun et al., 2012a). The isoprene emission capacity starts to develop just before full leaf photosynthetic competence, a pattern observed in velvet bean (Mucuna sp.; Kuzma & Fall, 1993; Harley et al., 1994) and aspen (Populus tremuloides; Monson et al., 1994). After reaching a maximum isoprene emission rate, the isoprene emission capacity starts to decline in senescing leaves (Kuhn et al., 2004; Sun et al., 2012a). These modifications are associated with changes in isoprene synthase gene expression and isoprene synthase protein content (Mayrhofer et al., 2005). Although isoprene synthase gene is ‘constitutively’ expressed, its promoter region contains circadian-, heat-, and stress-dependent elements, and the promoter activity depends on light and temperature over days to weeks (Loivamäki et al., 2007; Cinege et al., 2009).

A further important, and much less understood, driver that affects short- and long-term isoprene emissions is ambient [CO2]. Effects of growth [CO2] on isoprene emissions have been studied in different plant species under various experimental conditions with controversial outcomes. Elevated [CO2] had no or only a moderate effect on the isoprene emission capacity in Populus alba (Loreto & Velikova, 2001; Loreto et al., 2007), P. tremuloides (Calfapietra et al., 2008), and Populus × euramericana (Centritto et al., 2004), while elevated [CO2] resulted in enhanced isoprene emission capacity in Quercus rubra (Sharkey et al., 1991), Quercus pubescens (Tognetti et al., 1998), Gingko biloba (Li et al., 2009) and Populus tremula × P. tremuloides (Sun et al., 2012b). In other studies, elevated [CO2] led to a remarkable depression of isoprene emissions, including P. deltoides (Rosenstiel et al., 2003), Acacia nigrescens (Possell & Hewitt, 2011), Liquidambar styraciflua (Monson et al., 2007; Wilkinson et al., 2009), Populus tremuloides (Sharkey et al., 1991; Darbah et al., 2010), Eucalyptus globulus, P. tremuloides and P. deltoides (Wilkinson et al., 2009), Phragmites australis (Scholefield et al., 2004), and Platanus orientalis (Velikova et al., 2009). However, most studies on the inhibition of isoprene emission by elevated [CO2] were carried out at the leaf level and described mostly the response to instantaneously elevated [CO2], thereby mixing up the instantaneous CO2 response and the long-term acclimation response (see Sun et al., 2012b for a detailed discussion). In fact, the effects of elevated [CO2] on plants are multifaceted, involving instantaneous and acclimation metabolic responses at the leaf scale, and whole-plant processes such as acceleration of plant and leaf growth rates, leading to faster biomass accumulation, but also to alterations in stand development dynamics (Gielen et al., 2003; Rapparini et al., 2004; Arneth et al., 2007; Liberloo et al., 2007; Monson et al., 2007; Niinemets, 2010a). For constructing predictive models of isoprene emission under higher atmospheric [CO2], it is essential to consider plant acclimation and ontogeny.

Atmospheric [CO2] has been rising since the industrial revolution (Long et al., 2004; Rapparini et al., 2004; IPCC, 2007) and is predicted to continue to rise and to affect the global climate (Fuentes et al., 2000; Wiedinmyer et al., 2006). Yet, many models that predict isoprene emission from plants are based on empirical or semi-mechanistic algorithms (Guenther et al., 1993, 2006; Niinemets et al., 1999; Heald et al., 2009). These models usually utilize leaf-scale measurements and rely on meteorological input parameters as driving factors. To account for the effects of elevated [CO2], the models typically use an empirical parameterization based on measurements of instantaneous enhancements of [CO2] (Wilkinson et al., 2009). In several studies, it has been speculated that a possible increase in leaf area might cancel out the declining effect of instantaneous [CO2] elevation on isoprene emission (Rosenstiel et al., 2003; Centritto et al., 2004; Sun et al., 2012b). To our knowledge, this hypothesis has been tested with dense poplar stands at midseason when stand leaf area was the highest; in this study, leaf area increase at higher [CO2] moderated the leaf-level [CO2] effect by 15–50%, but did not fully offset the effect of reduced isoprene emission at leaf scale (Rosenstiel et al., 2003). However, at the canopy scale, the situation becomes further complicated by enhanced shading by increasing leaf area that might also reduce isoprene emission (see earlier). Thus, the stand-scale effect can strongly depend on ontogenetic characteristics. In rapidly developing more open stands, elevated [CO2] effects on leaf area can be more important than in fully closed stands exhibiting a steady-state leaf area index (LAI). Thus, for fast-growing stands, it is important to monitor the stand-level [CO2] response through the start of canopy development to closure.

In this study, we investigated carbon assimilation and isoprene emission in hybrid aspen (P. tremuloides × P. tremula) on canopy and leaf level from the start of canopy development to maturation under different ambient [CO2]. Our main aim was to test the hypothesis that the canopy isoprene emission of hybrid aspen grown under elevated [CO2] is increased even though an instantaneous effect of elevated [CO2] lowers isoprene emission at the level of individual leaves. We have previously demonstrated that growth under elevated [CO2] did not affect isoprene emissions when gauged under the same CO2 concentration (either ambient or elevated) at moderate-high light intensity (Sun et al., 2012b). Here we further use a modeling framework to quantitatively analyze the dynamics of canopy development among plants grown under current ambient and elevated [CO2].

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 material and growth system

Two-year-old saplings of hybrid aspen (Populus tremuloides Michx. × Populus tremula L.) clone H55 were selected for the experiments (Oksanen et al., 2001). The clone is a cross between a female P. tremula L. of Finnish origin and a male P. tremuloides Michx. of Canadian origin (Häikiö et al., 2009). H55 is widely used in Estonian and Finnish forestry as a fast-growing hybrid with moderate tolerance to ozone. The selected plants were c. 0.2 m tall and kept at −2°C in a dormant state before the experiments. Dormancy was broken by placing the plants in a growth room at 20°C 4 d before the start of the experiment. The saplings with swelling buds were potted in plastic pots (diameter 0.2 m, height 0.2 m) filled with 1 kg of sand and peat mixture (1 : 1) and installed in the open gas-exchange system consisting of four glass chambers of 12.5 l volume (diameter 0.2 m, height 0.4 m). Bud opening and leaf development took place inside the chambers. The plants were watered daily with tap water until the soil reached field capacity. To ensure optimum nutritional supply, the pots where initially fertilized with a slow-release fertilizer, and a liquid fertilizer was applied twice during the growth period as described in Sun et al. (2012b).

The glass chambers were connected to a gas-exchange system, allowing for continuous measurements of net assimilation, transpiration and isoprene emission rates (see Sun et al., 2012b for a detailed description of the system). Chambers 1 and 3 (Fig. 1) were kept at a CO2 concentration (average ± SD) of 380 ± 10 μmol mol−1 (hereafter denoted as ambient), while chambers 2 and 4 were treated with an elevated CO2 concentration of 780 ± 10 μmol mol−1 (hereafter denoted as elevated). Environmental conditions in the chambers were set for a 12 h photoperiod as described by Sun et al. (2012b). Temperature was maintained at 28–30: 23°C for day: night conditions, relative humidity at 60%, and light intensity at 800 μmol m−2 s−1 measured directly below the top boundary of the chambers. We repeated the experiment five times with 20 plants in total, 10 for ambient [CO2] and 10 for elevated [CO2] conditions.

image

Figure 1. Photograph of the computer-controlled growth chamber and gas exchange system used to control the ambient [CO2] during canopy development.

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Plant canopy leaf area estimation during the experiment

Leaf area growth during the experiment was assessed by a method combining digital photography and destructive harvesting. The plants in the chambers were photographed daily at a fixed time and from exactly the same position. The silhouette of the leaf area on each photograph was determined using GIMP (The GNU Image Manipulation Program, Version 2.6, www.gimp.org) by removing the background, the stem and petioles. During the first 1–3 d, the plant leaves were very small, and the ‘leaf area’ was defined as the area of swelled or partly opened buds. Within 30–40 d after the start of the experiment, the plants developed a canopy that filled the whole chamber volume. At that point, the experiment was stopped, the plants were removed, and all leaf blades were harvested and subsequently scanned to assess the total canopy leaf area at the end of each experimental run. In addition, we used data from 28 additional plants for calibration of digital photography. In these plants, we monitored the growth of all the individual leaves at daily intervals by tracing the outline of the leaves on paper and also taking digital photographs. The plants with different amounts of leaf area were harvested between 1 and 30 d after the start of the experiment. Based on these data, we developed a linear regression model relating the photographic silhouette leaf area and the scanned leaf area (Fig. 2). Mathematica 8 (Mathematica; Wolfram Research Inc., Champaign, IL, USA) was used to fit the data by a least-squares method. Estimating the projected leaf area from the silhouette leaf area may lead to a bias if the foliage aggregation varies during the experiment and/or among the treatments (Cescatti & Niinemets, 2004). Such variations in the degree of aggregation are expected to lead to curvilinearity or scatter in the regressions. However, in our study, there was no evidence of curvilinearity, and the relationships were strong when all data were pooled, suggesting that possible variations in the degree of spatial aggregation did not play a role in our study.

image

Figure 2. Calibration of the hybrid aspen (Populus tremula × Populus tremuloides) plant canopy leaf area by linear regression of photographically estimated foliage silhouette area (x-axis) and the scanned whole-plant true projected leaf area (y-axis) for plants of different ages. The regression equation is = 0.0012+ 2.17. The dashed lines denote the 95% confidence intervals for the mean.

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Online canopy net assimilation and isoprene emission measurements

The gas stream for the four parallel open gas-exchange chambers (see Fig. 1) was divided between the reference flow (the air entering the chamber) and the sample flow (the gas leaving the plant chamber). The analyzer ports were switched between the reference and sample modes, sequentially sampling the different chambers. Reference and sample flow gas concentrations were measured separately with an LI-7000 CO2/H2O analyzer (Li-Cor Inc., Lincoln, NE, USA) and a fast isoprene sensor (FIS; Hills-Scientific, Boulder, CO, USA). Each single chamber measurement lasted for 120 s (60 s for reference and 60 s for chamber flow). Thus one measurement cycle over four chambers lasted for 8 min. Isoprene concentration was recorded in 5 s intervals and CO2 assimilation in 30 s intervals. The FIS operates on the principle of chemiluminescence reaction between isoprene and ozone (as described in Monson et al., 1991; Zimmer et al., 2000; Pegoraro et al., 2005, 2006). The analyzer was calibrated frequently with a gas standard containing 5.74 ppm isoprene in N2, and operated as described previously (Rasulov et al., 2009).

From the reference and sample CO2 and isoprene concentrations, instantaneous canopy net assimilation (AC) and isoprene emission (IC) rates were obtained (Fig. 3a,b). By integrating the instantaneous rates, daily integrated canopy net assimilation (CO2, AC,day) and isoprene emission (IC,day) rates were calculated (Fig. 3a,b). In addition, net assimilation (A) and isoprene emission rates (I) per unit leaf area were calculated by dividing the whole-plant rates by the leaf area estimates for the given day (see the section, 'Modeling net assimilation and isoprene emission rates on the leaf scale').

image

Figure 3. Examples of diurnal variations in canopy net assimilation rate (a) and isoprene emission rate (b) in hybrid aspen (Populus tremula × Populus tremuloides). The data is stored in 5 s intervals and the daily integrated values are calculated according to the equations given in the figure.

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A dynamic model of canopy leaf area development, canopy assimilation rate and isoprene emission rate

Plant growth models have been developed for many different purposes. Generally, these models intend to describe the growth state of the whole plant, its organs or physiological processes in one life cycle (Yin et al., 2003). In classical plant growth analysis, a simple exponential growth model is commonly used (Evans, 1972; Causton & Venus, 1981; Hunt, 1982). However, the exponential model is only valid for the initial period of plant growth. The growth rate gradually slows down as plants accumulate nonphotosynthetic tissue and leaf area, resulting in greater respiration rate and higher self-shading (Evans, 1972; Causton & Venus, 1981; Hunt, 1982). Analogously, the rate of physiological processes levels off with increasing plant size (Coleman et al., 1993; McConnaughay & Coleman, 1999). To simulate the entire plant growth time series, several empirical growth models have been suggested. The Chapman–Richards function (Bertalanffy, 1957; Evans, 1972; Pienaar & Turnbull, 1973; Causton & Venus, 1981; Hunt, 1982; Liu & Li, 2003) is a widely used growth model which is based on the assumption that both the plants' physiological state and the environment affect the growth pattern. Assuming that positive assimilation or accumulation and negative dissimilation or consumption processes occur, the change of growth over time may be expressed as (Bertalanffy, 1957; Pienaar & Turnbull, 1973):

  • display math(Eqn 1)

where y denotes the size of the growing element (population, individual, organ) or changing process rate, α represents a positive and β a negative metabolic factor. The parameter m modulates the positive growth term and is usually related to environmental influences. After integration and application of the parameter transformations given by Eqns S2–S4 (in Supporting Information Methods S1), we can rewrite Eqn 1 to:

  • display math(Eqn 2)

where y(t) denotes the state of the measured variable at time t, y0 is the size of the growing component or rate of the process at time = 0, λ is the maximum increase of the growing resource, r is the relative growth rate, and c determines the curve shape. Even though the growth model (Eqn 2) is very flexible and can be fitted to different growth processes (Bertalanffy, 1957; Yin et al., 2003), independent estimations of model parameters may not always converge. The main reason for that behavior is evident in Eqns S1–S4 (in Methods S1), as the parameters λ, r and c all depend on m, and this interdependence may lead to collinearity.

We solved for the second-order derivative of Eqn 2 (see Methods S1) to estimate the time of fastest growth change at the inflection point of the curve and to determine the corresponding pair of function and argument values (yi, ti) as well as the maximum process rate (Ri). The model and parameters were used to fit the time-dependent changes in canopy leaf area, canopy net assimilation rate and canopy isoprene emission rate during the experiment.

Eqn 2 was used to describe the plant canopy leaf area development over time (see Fig. 4), time-dependent changes in daily integrated canopy net assimilation rate (AC,day) and isoprene emission rate (IC,day), and key parameters describing the dynamics of these canopy-level processes were derived using Mathematica 8 by a least-squares method.

image

Figure 4. Expansion of the hybrid aspen (Populus tremula × Populus tremuloides) plant canopy leaf area under ambient [CO2] of 380 μmol mol−1 (gray circles) and elevated [CO2] of 780 μmol mol−1 (white circles) over 35 d. The data are given as circles with error bars denoting the standard deviations (means ± SD). The solid line denotes the ambient [CO2] and the dashed line the elevated [CO2] modeled canopy leaf area as fitted by nonlinear least-squares regressions to Eqn 2 (r2 > 0.98, < 0.0001).

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Modeling net assimilation and isoprene emission rates on the leaf scale

Typically on a leaf scale, net assimilation and isoprene emission rate are given as fluxes (exchange rates per unit leaf area). We used the canopy-scale assimilation rate and isoprene emission rate divided by the leaf area in a given day to obtain the leaf-level fluxes. Canopy growth leads to shading of leaves within the canopy. Shading leads to changed environmental conditions in terms of light availability within the canopy and thus needs to be accounted for. Here, we have assumed that Eqn 2 remains valid and the loss of light energy through the canopy is caused by shading. We simulated the changes in light transmission arising as a result of time-dependent changes in canopy density according to the Lambert–Beer law (see Methods S1). Multiplication of Eqn S10 (in Methods S1) by Eqn 2 yields the leaf-level process rate as:

  • display math(Eqn 3)

We fixed the parameter Q0 to 400 μmol quanta m−2 s−1, which reflects the quantum flux density at half-height of the chamber at the time of plant installation in the chamber. The empirical parameter Q(t) is the transmitted quantum flux density at time t and z0 is the offset parameter (see Methods S1 for further details).

Leaf structural and chemical analyses

After the measurements were completed, the trees from each of the two treatments were harvested for structural and chemical analyses. Whole-canopy leaf area and fresh mass were estimated immediately after harvesting and leaf dry mass after drying at 70°C for at least 48 h. Foliage nitrogen (NM) and carbon content (CM) per unit dry mass were measured with a Vario MAX CNS analyzer (Elementar Analysen Systeme GmbH, Hanau, Germany). Finally, leaf dry : fresh mass ratio (DF), leaf dry mass per unit area (MA), leaf nitrogen (NA) and carbon content (CA) per unit leaf area were calculated.

Data analysis

Average whole-plant leaf morphological and chemical data and Eqn 2 model parameters for canopy- and leaf-level traits were compared among the treatments, elevated vs ambient, by paired t-tests with SPSS 17.0 (SPSS Inc., Chicago, IL, USA). Normality of the variables was always tested by Kolmogorov–Smirnov test. Altogether, 10 replicate estimates for every characteristic were available for both treatments. All statistical relationships were considered significant at < 0.05.

Results

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

Effects of elevated CO2 concentration on canopy leaf area development and foliage traits

Elevated [CO2] significantly increased canopy leaf area (Fig. 4), whole-canopy leaf dry mass (MC) and dry mass per unit leaf area (MA; Table 1) as compared with these traits in plants grown under ambient [CO2]. Carbon content per unit dry mass (CM) was not affected by the CO2 concentration during leaf growth, while carbon content per unit leaf area (CA) was increased significantly. Nitrogen content per unit dry mass (NM) was somewhat lower under elevated [CO2], and the C : N ratio was greater at elevated [CO2] (Table 1).

Table 1. Effects of growth [CO2] environment on mean (± SE) leaf anatomical and chemical traits in hybrid aspen (Populus tremula × Populus tremuloides) leaves
TraitTreatmentP-valueb
Ambient (380 μmol mol−1)Elevated (780 μmol mol−1)
  1. Ten independent samples (trees) were available for each treatment.

  2. a

    Significant differences between the means at < 0.05.

  3. b

    Means were compared by paired t-tests after testing for normality.

Whole-canopy leaf dry mass (MC, g per plant)1.64 ± 0.212.64 ± 0.14a0.003
Dry mass per unit area (MA, g m−2)28.5 ± 1.935.0 ± 1.5a0.03
Carbon content per unit dry mass (CM, %)43.29 ± 0.3343.53 ± 0.290.6
Carbon content per unit leaf area (CA, g m−2)12.4 ± 0.816.0 ± 1.1a0.02
Nitrogen content per unit dry mass (NM, %)2.34 ± 0.241.66 ± 0.13a0.03
Nitrogen content per unit leaf area (NA, g m−2)0.70 ± 0.0700.64 ± 0.0360.5
Carbon to nitrogen mass ratio19.0 ± 1.7026.2 ± 2.22a0.03

In our experiments, the onset of photosynthesis was observed within 2–4 d after plant installation in the growth chamber. The Chapman–Richards function fitted the temporal variation of canopy leaf area growth with high degree of explained variance (Eqn 2 and Fig. 4, r2 > 0.98, < 0.0001). The predicted asymptotic canopy leaf area was 43% greater under elevated [CO2] (942 cm2) than under ambient [CO2] (660 cm2; Fig. 4, Table 2). For plants grown under elevated [CO2], the relative leaf area growth rate was increased by 38% and the time of fastest growth, reached on the 12th day, was 2 d earlier than in the plants under ambient [CO2] (Table 2).

Table 2. Hybrid aspen (Populus tremula × Populus tremuloides) canopy leaf area development parameters (means ± SE) according to the Chapman–Richards model (Eqn 2)
 y0 (cm2)LA (cm2)r (d−1) c ti (d)Li (cm2)Ri (cm2 d−1)
  1. The parameters are defined as: the offset (y0), the maximal increase (LA), the relative growth rate (r) and the empirical parameter (c). The time (ti) and leaf area (Li) at the time of fastest growth as well as the maximal process rate (Ri) have been calculated according to Eqns S6–S8 (in Methods S1).

  2. a

    Significant difference between the mean values at < 0.05.

  3. b

    Differences in the mean values (= 10 for all parameters) were compared between the treatments by paired t-tests after normality was confirmed.

Ambient52 ± 8660 ± 540.13 ± 0.0116.5 ± 1.314 ± 1220 ± 1933.6 ± 3.2
Elevated71 ± 6942 ± 59a0.18 ± 0.021a8.2 ± 0.8a12 ± 1323 ± 20a67 ± 9a
P-valueb0.191< 0.00010.0330.0290.262< 0.00010.016

Canopy net assimilation and isoprene emission rates

Continuous diel recordings (see Fig. 3 for representative diel variations in net assimilation and isoprene emission rates) were used to calculate the daily net assimilation and isoprene emission rates. On the canopy scale, both integrated daily net assimilation and isoprene emission rates followed the dynamics of leaf area growth (Fig. 5), and Eqn 2 provided excellent fits to the temporal time-courses of both processes (Fig. 5, r2 > 0.98, < 0.0001). During the first 2–4 d, the plants respired until a sufficiently large leaf area was developed and leaves matured. The onset of isoprene emission was not substantially delayed as previously reported (Kuzma & Fall, 1993; Wiberley et al., 2005) and started about 1 d later than whole-canopy photosynthesis became positive.

image

Figure 5. Dynamics of measured and modeled hybrid aspen (Populus tremula × Populus tremuloides) canopy-scale physiological processes: daily net assimilation rate (a) and daily isoprene emission rate (b). Data are given as means ± SD. Gray circles, ambient[CO2] treatments; white circles, elevated [CO2] treatments. The lines denote nonlinear least-squares regressions to Eqn 2 (r2 > 0.98, < 0.0001), with the solid line representing ambient [CO2] and the dashed line elevated [CO2].

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Transformation of the model parameters according to Eqns S6–S8 (in Methods S1) allows for estimation of relevant physiological characteristics of canopy maturation (Fig. 5, Table 3). Canopy net assimilation rate increased faster, but not earlier, under elevated [CO2], and reached a maximum value of 32 mmol d−1, almost double that under ambient [CO2] (16 mmol d−1; Fig. 5a, Table 3). The maximum slope (Ri) of the canopy net assimilation was found on the 12th day for both treatments (Table 3), but the plateau value (90% of maximum) was reached at day 22 in the case of elevated [CO2] and day 33 in the case of ambient [CO2]. On average, the plants under the elevated [CO2] had 1.4 times higher relative daily growth rate than the plants under ambient conditions.

Table 3. Temporal dynamics of hybrid aspen (Populus tremula × Populus tremuloides) whole-canopy assimilation and isoprene emissions. Mean (± SE) parameters of canopy-scale daily net assimilation and isoprene emission rates fitted by Eqn 2
 y0 (mmol d−1)Amax,canopy (mmol d−1)r (d−1) c ti (d)Ai (mmol d−1)Ri (mmol d−2)
Net assimilation
Ambient−0.95116.0 ± 0.90.17 ± 0.0179.7 ± 2.612 ± 15.36 ± 0.371.07 ± 0.07
Elevated0.43232.0 ± 0.9a0.25 ± 0.035a31 ± 9a12 ± 111.33 ± 0.43a3.07 ± 0.43a
P-valueb0.233< 0.000010.0210.0320.684< 0.000010.003
 y0 (mmol d−1)Imax,canopy (μmol d−1)r (d−1) c ti (d)Ii (μmol d−1)Ri (μmol d−2)
  1. Amax,canopy denotes the maximal increase in daily assimilation rate, and Imax,canopy denotes the isoprene emission rate; the other parameters (y0, r, c) have the same meaning as in Table 2. Parameters for the time (ti) and process value (Ai or Ii) at the point of fastest growth and the maximal process rate Ri were calculated as means ± SE according to Eqns S6–S8 (in Methods S1).

  2. a

    Significant difference between the mean values at < 0.05.

  3. b

    Differences in the mean values (= 10 for all parameters) were compared between the treatments by paired t-tests after normality was confirmed.

Isoprene emission
Ambient0.00027.2 ± 1.80.238 ± 0.01239 ± 815 ± 19.8 ± 0.72.45 ± 0.26
Elevated0.00037.6 ± 2.2a0.220 ± 0.01423.2 ± 4.5a14 ± 113.4 ± 0.8a3.11 ± 0.23a
P-valueb 0.0020.3260.160.3860.0030.031

The maximum canopy isoprene emission rate was 1.4-fold higher for plants under elevated [CO2] (38 vs 27 mol d−1; Fig. 5b, Table 3). The relative growth rates of isoprene emission were not significantly different for both treatments but the time of fastest growth differed by 1 d: day 14 for elevated [CO2] and day 15 for ambient [CO2].

Leaf-scale net assimilation and isoprene emission fluxes

The process rates expressed per unit leaf area highlighted two important points. First, the isoprene emission flux was lower under elevated [CO2] and, secondly, the shape of the developmental dynamics was changed and the curves exhibited a maximum. The decreases in flux rates beyond the maxima (Fig. 6) were assumed to be caused by increasing self-shading within the growing canopy. Thus, the data were better described by Eqn 3, which considered the increased shading during canopy expansion (Table 4). The maxima of net assimilation flux were observed at about day 18 in both treatments (Fig. 6), but elevated [CO2]-grown plants had around a 1.4-fold higher maximum assimilation rate than ambient [CO2]-grown plants (8.7 vs 6.1 mol m−2 s−1; Fig. 6, Table 4).

Table 4. Temporal variation in hybrid aspen (Populus tremula × Populus tremuloides) leaf-scale net assimilation and isoprene emission fluxes according to the modified Chapman–Richards model (Eqn 3)
 Q(t) (μmol m−2 s−1)z0 (μmol m−2 s−1)Amax,leaf (μmol m−2 s−1)r (s−1) c ti (d)Ai (μmol m−2 s−1)Ri (μmol m−2 s−2)
Net assimilation
Ambient4.44 ± 0.35−0.10 ± 0.014.6 ± 0.60.193 ± 0.0195.6 ± 2.09 ± 12.57 ± 0.130.86 ± 0.12
Elevated3.83 ± 0.20−0.27 ± 0.04a6.1 ± 0.4a0.211 ± 0.013a6.9 ± 1.29 ± 13.62 ± 0.31a1.23 ± 0.19a
P-valueb0.1430.0130.0060.0490.0850.8140.0050.002
 Q(t) (nmol m−2 s−1)z0 (nmol m−2 s−1)Imax,leaf (nmol m−2 s−1)r (s−1) c ti (d)Ii (nmol m−2 s−1)Ri (nmol m−2 s−2)
  1. Q(t), the change in canopy light transmission; z0, an offset parameter; Amax,leaf, the leaf scale maximum net assimilation flux; Imax,leaf, the maximum isoprene emission flux; parameters r and c are as defined in Table 2; the maximal process rate (Ri) is calculated at the inflection point (ti, Ai or Ii) of the rising part of the curve.

  2. a

    Significant difference between the mean values at < 0.05.

  3. b

    Differences in the mean values (= 10 for all parameters) were compared between the treatments by paired t-tests after normality was confirmed.

Isoprene emission
Ambient3.99 ± 0.220.00010.5 ± 0.40.158 ± 0.0097.6 ± 1.312 ± 15.43 ± 0.071.34 ± 0.14
Elevated2.56 ± 0.36a0.0005.9 ± 1.0a0.141 ± 0.0095.3 ± 0.5a11 ± 13.14 ± 0.42a0.69 ± 0.17a
P-valueb0.009 0.0010.1380.0050.4490.0030.037
image

Figure 6. Time courses of net assimilation flux (a) and isoprene emission flux (b) in hybrid aspen (Populus tremula × Populus tremuloides) rescaled to leaf scale for different [CO2] treatments (gray circles, ambient [CO2]; white circles, elevated [CO2]). Data are given as means ± SD. The leaf-scale values were obtained from canopy-scale estimates by dividing the daily integrated process rates by the daily leaf area and correcting for the within-canopy shading (Eqn 3). The lines (solid, ambient [CO2]; dashed, elevated [CO2]) were calculated by nonlinear least-squares regressions to Eqn 3 (r2 > 0.98, < 0.0001).

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Maximum isoprene emission flux was observed at day 25 under elevated [CO2], and at day 23 under ambient [CO2], and the maximum flux was 1.3-fold lower under elevated [CO2] than under ambient [CO2] (9.1 vs 12.7 nmol m−2 s−1; Fig. 6). While the net assimilation fluxes were approximately of the same shape regardless of the growth environment, the isoprene emission fluxes showed distinct dynamic behaviors among the treatments. The maximum isoprene emission flux rates occur at different times, with the elevated [CO2]-grown plants being about 2–3 d delayed, which is remarkable, as the inflection point ti was only 1 d ahead.

Discussion

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

Effects of elevated [CO2] on leaf traits and canopy development

Many previous studies that focused on plants grown under elevated [CO2] have suggested that there is a link between ‘up-regulation’ and ‘down-regulation’ of leaf traits and carbon uptake (Luo et al., 1998; Nowak et al., 2004). In this study, the elevated [CO2] treatment resulted in a higher maximum leaf area and leaf dry mass on the canopy scale as well as a higher leaf dry mass per unit area (Table 1), which is in line with previous findings on the effects of elevated [CO2] (e.g. Sims et al., 1998a,b; Miyazawa et al., 2011). According to the fitted parameters characterizing canopy leaf area development, elevated [CO2] stimulated the leaf area growth 1.4-fold. Together with doubled canopy-scale assimilation rate (Fig. 5) and the reported increase in leaf starch content (Sun et al., 2012b), this suggests that elevated [CO2] enhances the carbon supply for leaf construction, induces morphological changes and alters metabolic processes. In our study, plants grown under elevated [CO2] had significantly higher foliage carbon content on a leaf area basis but not on a dry mass basis. Foliage nitrogen content showed the opposite response, with lower content on a dry mass basis but not on a leaf area basis. This is in agreement with earlier findings that, for a given nutrient supply, leaf N content per unit mass is reduced under elevated [CO2] (Liu et al., 2005).

Despite lower N content per unit dry mass, leaf area growth can still be enhanced under elevated [CO2]. Taylor et al. (2008) observed a greater rate of canopy leaf area formation in establishing canopy, resulting in overall higher canopy LAI for the whole vegetation period. There is further evidence demonstrating that plants grown under elevated CO2 maintain greater leaf area over time unless feedbacks as a result of soil nutrient limitations start to constrain foliage growth (Gielen et al., 2003; Norby et al., 2005; Luo et al., 2006; Liberloo et al., 2007). Our study further suggests that elevated [CO2] is a key factor during canopy leaf area development. In particular, the maximum growth rate was doubled under elevated [CO2] (Fig. 4, Table 2).

Increased daily net assimilation and isoprene emission rates on canopy level

Effects of growth [CO2] on leaf-level net assimilation and isoprene emission rates have been reported in several studies (see the 'Introduction' and Centritto et al., 2004; Possell et al., 2005; Wilkinson et al., 2009; Possell & Hewitt, 2011; Sun et al., 2012b). It has often been speculated that the down-regulation of isoprene emissions by elevated [CO2] might be balanced by enhanced leaf area growth. The work of Possell et al. (2005, 2010), Possell & Hewitt (2011) and Centritto et al. (2004) suggested that, on a canopy or whole-plant level, no significant down-regulation in isoprene emission was seen, but in Rosenstiel et al. (2003), canopy-level isoprene emissions were also reduced under elevated [CO2]. In our study, the daily isoprene emission rate was increased by a factor of 1.4 in plants grown under elevated [CO2] as compared with plants grown in current ambient [CO2]. Furthermore, the daily net assimilation rate was found to be doubled. Given the general enhancement of photosynthetic production and the overall moderate fraction of carbon going into isoprene synthesis (Sharkey & Yeh, 2001), differences in the supply of precursors for the isoprene synthesis seem to be unlikely across the studies. In fact, study-to-study differences in the degree of enhancement of foliage area expansion growth seem to provide an explanation for study-to-study differences in the patterns observed. Although leaf area increase moderated the leaf-level inhibition by elevated [CO2] at the canopy scale, a much lower leaf area increase was observed in the study of Rosenstiel et al. (2003) than in our study.

The application of the growth model further emphasized that both canopy-scale net assimilation and isoprene emission rates followed leaf area developmental dynamics. This is in agreement with suggestions that isoprene emission could be controlled by the whole-plant carbon allocation pattern rather than by the availability of photosynthetically fixed carbon (Funk et al., 1999). There is further evidence that part of the carbon emitted as isoprene comes from ‘old’ stored carbon (Kreuzwieser et al., 2002; Trowbridge et al., 2012), and thus, not only growth and photosynthesis, but also growth and isoprene emission can be partly regulated at the level of soluble carbon pools. In this context, it is relevant that elevated [CO2] can shift the contributions of ‘old’ and recently fixed carbon to isoprene emission (Trowbridge et al., 2012).

Downscaling to leaf-level processes

If the data are normalized per unit leaf area, the canopy processes can be scaled down to leaf level. As leaves are shaded by each other in a canopy and emission capacities acclimate to different environmental conditions inside the canopy, we emphasize that the canopy-scale rates calculated per unit leaf area are not directly comparable to single leaf measurements (Niinemets et al., 2010a; Niinemets, 2012). Nevertheless, these ‘leaf scale’ estimates demonstrate the efficiency of unit leaf area for net assimilation and isoprene emission as determined by their prevailing environmental conditions in the canopy and metabolic capacity.

While the net assimilation flux at the leaf level was still enhanced by a factor of 1.4 under elevated [CO2], the opposite was found for isoprene emission fluxes. Per unit leaf area, the maximum isoprene emission fluxes, adjusted to a changed light environment during leaf growth (Eqn 3), were c. 30% lower in plants grown under elevated [CO2]. Given that total leaf area increased by a factor of 1.4, and the canopy isoprene emission rate was increased by the same factor, one might argue that there should be no effect if scaled to unit leaf area. However, such an argument is misleading, because of strongly nonlinear responses of isoprene emissions to light, implying that the contribution of upper canopy leaves is disproportionately larger than that of lower canopy leaves (Cescatti & Niinemets, 2004; Niinemets et al., 2011; Niinemets, 2012). Furthermore, this ‘canopy effect’ changed with the expansion of plant canopy, underpinning the argument that canopy developmental state played an important role in affecting the average ‘efficiency’ of isoprene synthesis.

Furthermore, treatment-dependent changes in this dynamic behavior constitute an important result. In particular, earlier onset of reduction of the maximum flux in ambient [CO2] leads to a less prominent difference between both treatments (Fig. 6). This difference might reflect earlier cessation of leaf growth and maturation under ambient [CO2]. Thus, despite enhanced self-shading, the plants under elevated [CO2] likely possessed a greater foliage area fraction that was still developing; the isoprene emission rate of these leaves was still increasing, while the emission capacity of all leaves in plants under ambient [CO2] had already reached the maximum value.

The differences in net assimilation and isoprene emission in whole-canopy vs leaf-scale responses (enhancement of net assimilation at both canopy and leaf scales and enhancement of isoprene emission at canopy and reduction at leaf scale) and differences in temporal dynamics at the leaf scale emphasize the important difference in the control of photosynthesis and isoprene emission by light and CO2 concentration. Light sensitivity, and thus responsiveness to within-canopy light gradients of net assimilation, decreases with increasing [CO2] as a result of improved quantum yield, while the light sensitivity of isoprene emissions increases with increasing [CO2] (Sun et al., 2012b). Thus, complex interactions among canopy expansion, self-shading, leaf development and process dependence on light and [CO2] collectively explain the differences in canopy- and leaf-level net assimilation and isoprene emissions.

What can we learn from the canopy-scale dynamics for large-scale isoprene emission modeling?

All recent approaches to model the impact of atmospheric [CO2] on isoprene emissions are based on data on single leaf measurements expressed either per unit leaf area or per unit dry mass (Possell et al., 2005; Wilkinson et al., 2009; Possell & Hewitt, 2011). This is especially interesting as Possell et al. (2005, 2010) and also Pegoraro et al. (2005, 2006) were measuring whole-canopy gas exchange, but their model extensions of the Guenther et al. (1993, 1995) algorithm were based only on leaf area scaled measurements. Furthermore, extensive within-canopy variation in isoprene emission potentials (Harley et al., 1996; Funk et al., 2006; Niinemets et al., 2010b) as well as greater light sensitivity of isoprene emission in plants grown under elevated [CO2] (Sun et al., 2012b) have not been considered. Use of a single leaf-scale emission estimate without considering modifications in canopy leaf area and within-canopy variation patterns, and altered light sensitivity, implies that single-leaf and whole-canopy growth [CO2] responses will always be the same. As our results demonstrate, a leaf-scale reduction in isoprene emission does not necessarily correspond to canopy-scale reduction. The quality of the upscaling procedure from leaf to canopy, including the inherent within-canopy variation in emission capacity and light sensitivity, and, over the long term, consideration of leaf area dynamics, determines whether or not the canopy-scale modeled emissions will match the measurements. Therefore, a very first task should be to test whether the upscaled model estimations are in agreement with the measured values on the canopy scale.

Using a classic growth model (Eqns 1,2 and S1–S8), we have shown that the developmental dynamic is an important factor to consider in fast-growing canopies. The key processes (leaf area growth, net assimilation, and isoprene emission rates) reached a stable state within 2–3 wk at the canopy level. This allows us to give robust estimates on the relative change of the process dynamics for plants grown under different [CO2] treatments. As our approach excluded severe stresses, these estimates may correspond to an optimum situation and may need modification to account for stress events under natural field conditions. Nevertheless, isoprene emission is much less sensitive to stress than net assimilation rate, and may even actually increase under mild drought and ozone stress (Loreto & Schnitzler, 2010; Niinemets, 2010a). At any rate, we suggest the use of information available on the canopy scale to constrain and verify model estimations that scale up from the leaf to canopy.

Scaling down from canopy to leaf allows for further insight into canopy-level modifications. Although one can simply calculate the emission rate per unit leaf area as the rate of canopy emission divided by canopy leaf area, the resulting variable carries no physiological meaning, because of within-canopy gradients in light and strongly nonlinear responses of isoprene emission to light. We note that in some early isoprene emission models, such an approach for scaling has been used (Pierce & Waldruff, 1991; Owen et al., 2003), but as a result of integration errors, it is discouraged. To account for within-canopy changes, we included light gradient in the growth model that result in more or less correct inversion of the canopy-level emissions (Eqn 3, Fig. 6).

It has been suggested that, on the canopy scale, leaf-to-leaf differences are inherently integrated and, therefore, that scale may be more appropriate to model large-scale emission estimates as currently recommended by MEGAN (Guenther et al., 2006). However, model parameters used in canopy-scale models also must come from canopy-scale measurements rather than from leaf-level estimates to avoid scaling errors (Niinemets et al., 2010a for a discussion).

Conclusions

Our results show that, in hybrid aspen, the canopy-scale isoprene emission rate under elevated [CO2] significantly exceeded that under ambient [CO2]. The main reason for this difference was the stimulated growth of the canopy leaf area, which more than compensated for biochemical down-regulation of the isoprene synthesis pathway. We also showed that a portion of the inhibition of isoprene emission by elevated [CO2] may be caused by the enhanced leaf area growth, if rescaled from canopy to leaf scale, resulting from acclimation to enhanced shading and lower within-canopy light intensities. However, greater responsiveness of isoprene emissions to light under elevated [CO2], as demonstrated in a previous study (Sun et al., 2012b), likely compensated for the reduced light intensity. Furthermore, different temporal dynamics of leaf-level estimates suggested different age structure of leaf populations among elevated and ambient [CO2]. Thus, modeling canopy isoprene emissions without considering within-canopy patterns in leaf age, acclimation capacity and responsiveness to light is very problematic. In particular, use of ‘average emission factors’, one for elevated [CO2] and one for ambient [CO2], for upscaling to the canopy is not to be recommended, and might be very misleading.

Overall, we suggest that predictions of future isoprene emission responses to elevated [CO2] should more explicitly consider canopy-scale processes. For regional- or global-scale estimations of isoprene emissions, we recommend the use of canopy-scale data, and encourage more experimental and modeling work to obtain these data. We also suggest that large-scale free air CO2 enrichment (FACE) studies are needed to monitor long-term changes in canopy structure (LAI and biomass) in response to CO2 enrichment and couple this to isoprene emission measurements.

Acknowledgements

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

Financial support for the study was provided by the Estonian Ministry of Science and Education grant (SF1090065s07), the Estonian Science Foundation (grants 9253 and 8110), the European Commission though the European Regional Fund (the Center of Excellence in Environmental Adaptation, the Environmental Conservation and Environmental Technology R&D Programme: BioAtmos), through the European Social Fund (Doctoral Studies and Internationalization Programme DoRa), and the Human Frontier Science Program (www.hfsp.org).

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  2. Summary
  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

Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

FilenameFormatSizeDescription
nph12200-sup-0001-MethodsS1.docWord document47KMethods S1 Eqns S1–S4, the detailed form of the integrated Eqn 1 and parameter transformations to reach to Eqn 2; Eqns S5–S8, the detailed solution of the second derivative of Eqn 2 and calculations of key parameters of fastest growth rate and time of fastest growth; Eqns S9–S12, details to connect the Lambert–Beer law to Eqn 2.