Hans R. Schultz. Functional Plant Biology, 2003, 30,

Transcription

1 CSIRO PUBLISHING Functional Plant Biology,,, 7 87 Extension of a Farquhar model for limitations of leaf photosynthesis induced by light environment, phenology and leaf age in grapevines (Vitis vinifera L. cvv. White Riesling and Zinfandel) Hans R. Schultz Institut für Weinbau und Rebenzüchtung, Fachgebiet Weinbau, Forschungsanstalt, von Lade Straße 1, D- Geisenheim, Germany. h.schultz@fa-gm.de Abstract. Measurements of gas exchange and stomatal conductance were made on potted and field-grown grapevines (Vitis vinifera L.) on leaves from different light environments (sun and shade) at different phenological stages during the season to parameterise the Farquhar model. The model parameters for Rubisco activity (V cmax ), maximum electron transport rate (J max ), and triose-phosphate utilisation (TPU) were estimated on the basis of a large data set (n = 1) of CO assimilation (A) versus internal CO pressure (C i ) curves. Leaf age was described with the leaf plastochron index (LPI). Stomatal coupling to photosynthesis was modelled with the Ball Woodrow Berry empirical model of stomatal conductance. Mature shade leaves had % lower values of V cmax, J max and TPU than sun leaves. The difference between leaf types decreased at the end of the season. The ratio J max /V cmax and values of day respiration (R d ) and CO compensation point in the absence of mitochondrial respiration (Γ*) varied little during the season and were independent of LPI. Validation of the model with independent diurnal data sets of measurements of gas exchange and stomatal conductance at ambient CO concentrations for three days between June and October, covering a large range of environmental conditions, showed good agreement between measured and simulated values. Keywords: gas exchange, leaf age, light environment, modelling, phenology, stomatal conductance, Vitis vinifera. Introduction The geometrical structure of a plant canopy determines its interaction with fluxes of energy. Canopy architecture and density are intimately related to crop productivity since the distribution of leaf and non-leaf surfaces influences light interception, local light microclimates and subsequent carbon assimilation and water loss, which may vary diurnally, daily and seasonally. This has been widely recognised as being important for fruit and grape production (Wagenmakers 1991; Dokoozlian and Kliewer 199). Since the large spatial and temporal variations in the radiation regime in different locations of a canopy are difficult to measure, simulation models have become the main tool to integrate the activities of individual leaves and their responses to the natural environment and to evaluate the performance of various plant canopy forms. In most models a scale-up approach from the leaves to the canopy is used (Caldwell et al. 198; Harley and Baldocchi 199; Wilson et al. 1) where leaf physiological parameters are described first and then integrated over the whole canopy. On the leaf level, the gas-exchange model of Farquhar et al. (198) and Farquhar and von Caemmerer (198) has been incorporated into models scaling from single leaves (Day and Parkinson 198; Harley et al. 198) to the canopy (Caldwell et al. 198; Wang and Jarvis 199) to global climate simulations (Sellers et al. 199). Despite considerable research on grapevine photosynthesis, and some recent attempts to model grapevine photosynthesis and stomatal behaviour (Jacobs et al. 199), the Farquhar model has never been fully parameterised for this species and has only recently been used to quantify the effects of drought on leaf biochemistry (Maroco et al. ). The problem for parameterisation of the Farquhar model is that very often the necessary values of photosynthetic capacity can only be derived from a few samples (Harley and Baldocchi 199) obtained during brief periods of the Abbreviations: A, net CO assimilation; C a, external CO partial pressure; C i, intercellular CO partial pressure; g s, stomatal conductance; J max, maximum electron transport rate; k, stomatal sensitivity factor; LPI, leaf plastochron index; O, oxygen concentration; PP I VI, phenological phases I to VI; PPFD, photosynthetic photon flux density; R d, day respiration; R n, night (dark) respiration; RuBP, ribulose-1,-bisphoshate; TPU, triose-phosphate utilisation; V C, rate of carboxylation of Rubisco; V cmax, maximum Rubisco activity; V O, rate of oxygenation of Rubisco; W c, quantity, kinetic properties and activation state of Rubisco; W j, RuBP regeneration in the Calvin cycle; W p, availability of inorganic phosphate. CSIRO 1.171/FP1 1-8//7

2 7 Functional Plant Biology H. R. Schultz season, and/or photosynthetic parameters are assumed invariant with the growing season or inferred from the literature (Amthor et al. 199). For plants that form complex heterogeneous canopies, such as grapevines, and that possess a multitude of age populations at any given time during the season, a more comprehensive approach for establishing the model seems necessary. To interpret and simulate the temporal behaviour of such a system requires an understanding of the time evolution of processes that are dependent on leaf age. Temporal patterns of leaf aging are often neglected in modelling studies but have recently gained more attention in tree physiology [see special issues on this topic edited by Jarvis and Magnani () and Bond ()]. In a series of studies on the seasonal trends of photosynthetic capacity in deciduous forests (Ellsworth ; Wilson et al. a, b, 1), it has been recognised that by omitting the aging trends and seasonal variation, annual carbon uptake may be seriously overestimated (by up to %; Wilson et al. 1). In addition, differences in light exposure during the development of single leaves may modify the photosynthetic apparatus and alter patterns of photosynthesis during leaf development and aging (Jurik et al. 1979; Cartechini and Palliotti 199). Depending on the system, leaf area density (LAD) in grapevine canopies can locally reach up to m m in extreme cases, indicating intensely shaded zones (Schultz et al. 1). Leaf morphology and physiology with respect to the photosynthetic apparatus are likely to change in a continuous manner with reduction in growth photosynthetic photon flux density (PPFD) (Caldwell et al. 198; Meir et al. ), yet are rarely incorporated into models in that detail (Lloyd et al. 199; Niinemets and Tenhunen 1997). In this paper, leaf-scale measurements and parameterisation of the Farquhar model for grapevine leaves of different age, at different phenological stages during the season, and from different light environments are described. The terms sun and shade leaves are used here without further differentiation based on earlier positive results in parameterising such a model for deciduous forests and scaling this model up to whole canopies (Harley and Baldocchi 199; Baldocchi and Harley 199). Materials and methods In the present study, data material acquired over the course of a decade of experiments under different set-ups in the laboratory and the field in the USA, France and Germany were assembled and analysed. The Farquhar model For C plants the model of CO assimilation rate, A (Farquhar et al. 198), can be written as: A = V C.V O R d = V C 1 Γ* R, d C i (1) where V C and V O are the rates of carboxylation and oxygenation of Rubisco, C i is the CO partial pressure in intercellular spaces, and R d is the rate of CO evolution in the light (day respiration) resulting from processes other than photorespiration. The term Γ* denotes the CO compensation point in the absence of dark respiration and is inversely related to τ, the Rubisco specificity factor for CO /O, through Γ* =.O/τ, where O is the oxygen concentration (Harley and Tenhunen 1991; Bernacchi et al. 1). Values for Γ* can be determined by in vivo measurements (Brooks and Farquhar 198). The rate of carboxylation, V C, is assumed to be limited by one of three factors: (1) quantity, kinetic properties and activation state of Rubisco (W c ); () ribulose-1,-bisphoshate (RuBP) regeneration in the Calvin cycle (W j ); and () the availability of inorganic phosphate (W p ) (Farquhar et al. 198; Sharkey 198). That is, V C = minimum(w c, W j, W p ). The rate of carboxylation limited by the amount, activation state and kinetic properties of Rubisco can be expressed as: V cmax C i W C =, () C i + K C (1 + O/K O ) where V cmax is the maximum rate of carboxylation and K C and K O are the Michaelis Menten constants for carboxylation and oxygenation, respectively. The rate of carboxylation limited solely by the rate of RuBP regeneration is mediated by the rate of electron transport through photosystem II (J): JC i W () j =, (C i + Γ*) where four electrons are assumed to generate sufficient ATP and NADPH for the regeneration of RuBP (Farquhar and von Caemmerer 198). Electron transport rate depends on incident light intensity, PPFD (µmol m s 1 ), based on Smith (197): J = αppfd, α PPFD 1 + J max where α is the efficiency of light conversion related to incident light (mol electrons per mol photons), and J max is the maximum lightsaturated rate of electron transport. W p, the rate of carboxylation limited by inorganic phosphate availability, is given by: W p = TPU + V C Γ*, C i where TPU is the rate of triose-phosphate utilisation (sucrose and starch production) (Sharkey 198). The temperature dependence of K C and K O can be described by an exponential function using the parameters published by Harley et al. (199) and based in part on Jordan and Ogren (198) according to: Parameter(K C, K O ) = exp{c [ H a /(RT k )]}, () where c is a scaling constant, H a is the activation energy, R is the gas constant (.81 kj K 1 ), and T k is the leaf temperature in degrees Kelvin. The temperature dependence of V cmax, J max and TPU can be described in partial analogy to eqn according to Harley and Tenhunen (1991), based on the original equation by Johnson et al. (19): exp{c [ H a /(RT k )]} (V (7) cmax, J max, TPU) =, 1 + exp[( ST k H d )/(RT k )] where H d is the energy of deactivation and S is an entropy term (Harley and Tenhunen 1991; Harley et al. 199). () ()

3 A model of limitations on leaf photosynthesis Functional Plant Biology 7 In addition, the dependence of R d and Γ* on leaf age was included. Leaf age was defined with the leaf plastochron index (LPI) (Erickson and Michelini 197) and the relationship R d as a function of LPI was described separately for sun and shade leaves with: R d (LPI) = a 1 exp(a LPI) + a, (8) where a 1, a and a are parameters describing the shape and the y-axis offset of the curve. The age dependence of R n and Γ* can be described in analogy to eqn 8. The relationship of Γ* to LPI is linear and independent of the light environment: Γ*(LPI) = b 1 + b LPI, (9) where b 1 and b are scaling parameters. Equations and parameters describing the temperature dependence of R d and Γ* were taken from Kirschbaum and Farquhar (198) and Brooks and Farquhar (198) and combined with eqns 8 and 9 to yield for R d : R d (T k ) = R d (LPI)[1 + d 1 (T k.1) + d (T k.1) ], (1) and Γ*: Γ*(T k ) = Γ*(LPI) + e 1 (T k.1) + e (T k.1), (11) where.1k (7.1 C) was the reference temperature at which R d and Γ* as a function of LPI were determined and d 1, d, e 1 and e are parameters to describe the relative temperature dependence (Kirschbaum and Farquhar 198) (Table 1). Equation 1 assumes that the shape of the temperature response of R d is independent of the LPI. Stomatal conductance to water vapour (g s ) was modelled with the approach of Ball et al. (1987): h g s = g o + ka, (1) C a where g o is a residual stomatal conductance to H O vapour (A when PPFD ), and k is termed the stomatal sensitivity factor, representing the composite sensitivity to assimilation, CO concentration, humidity and temperature (Ball et al. 1987; Harley and Tenhunen 1991). Measurements of relative humidity (h) and CO partial pressure (C a ) outside the leaf boundary layer were used to drive the stomatal model. For the biochemical model, the driving variable C i was calculated according to C i = C a 1.A/g s, where the factor 1. corrects for the difference in diffusivity between CO and H O. Plant material and growth conditions Laboratory experiments Some experiments were conducted at the University of California, Davis, USA. Two separate batches of -year-old grapevine plants (Vitis vinifera L. cvv. Zinfandel and White Riesling) were grown in the greenhouse (April August) or outdoors (August December) in 1991 and 199 in -L pots containing a soil:peat:perlite mixture (1::). Growth conditions in the greenhouse were C during the day and 18 C during the night, a relative humidity of > % and a 9 1-h photoperiod. Plants were grown outdoors late in the year to simulate Table 1. List of model parameters and the parameters used to describe their temperature dependence Values in parentheses are derived from data in the literature (Jordan and Ogren 198; Kirschbaum and Farquhar 198; Brooks and Farquhar 198; Harley et al. 199); all other values are determined from measured data as described in the text Temperature Sun Shade Parameter Units parameters leaves leaves Units K C Pa CO c(k C ) (.79) H a (K C ) (8.7) kj mol 1 K O kpa O c(k O ) (9.9) H a (K O ) (1.1) kj mol 1 Γ* Pa CO e 1 (1.88) e (.) R d µmol CO m s 1 d 1 (.8) d (.) V cmax µmol CO m s 1 c(v cmax )..7 H a (V cmax ) kj mol 1 H d (V cmax ) kj mol 1 S(V cmax ).. kj K 1 mol 1 J max µmol electrons m s 1 c(j max ) H a (J max ) kj mol 1 H d (J max ) kj mol 1 S(J max ).7.9 kj K 1 mol 1 TPU µmol CO m s 1 c(tpu)..9 H a (TPU) kj mol 1 H d (TPU) kj mol 1 S(TPU)..9 kj K 1 mol 1 α mol electrons per mol photons (1 C).. ( C).19. ( C).19. ( C).1.1 (> C).1.1 g mmol H O m s 1 1. k mmol H O mbar CO per µmol CO 118.9

4 7 Functional Plant Biology H. R. Schultz temperature conditions in a cool climate usually encountered by field plants before harvest. In each experiment, eight plants were grown under full sunlight [> 1 µmol m s 1 (maximum PPFD); > mol m d 1 integrated PPFD as determined with a Li-Cor 19s Quantum sensor, Li-Cor, Lincoln, Nebraska, USA] and eight plants were grown under a neutral shade screen (< µmol m s 1 (maximum PPFD) and < 1 mol m d 1 integrated PPFD). About 1 week after bud break, all plants were thinned to two shoots with at least one inflorescence per shoot. Physiological age Physiological leaf age was defined with the LPI. The plastochron concept (Erickson and Michelini 197) is suitable for the description of age-related changes in sun and shade leaf photosynthesis of grapevines (Schultz 199). Leaves on secondary, lateral shoots were classified into apical (young) (upper leaves on a shoot) and basal (old) leaves only. Field experiments Some experiments on leaf gas exchange were conducted in the field in Villeneuve-les-Maguelonne near Montpellier, France ( ), and at the Research Institute in Geisenheim, Germany ( , 1997), both with the Riesling cultivar. Plants in Villeneuve-les- Maguelonne were 1 years old, and those at Geisenheim 9 years old when first used for the experiments. Leaf gas-exchange measurements Laboratory gas-exchange measurements Measurements of the relationship of A to C i were conducted under saturating PPFD in the morning between 8 and 1 hours with an open-system gas-exchange apparatus, previously described by Sims and Pearcy (1989), on potted plants grown in the greenhouse or outdoors. Measurement series were conducted during six phenological phases: PP I, bud break to bloom; PP II, bloom to berries at pea size; PP III, berries at pea size to end of berry growth phase I; PP IV, veraison (start of berry ripening) until 1 week after veraison; PP V, mid-maturity ( weeks after veraison); and PP VI, 1 week before harvest to harvest. Leaf temperature was controlled at 7.1 ±. C and vapour pressure deficit between leaf and air was maintained at. 1.1 kpa. Air of a given CO partial pressure was obtained by mixing CO -free air with air containing % CO using mass flow controllers. The light source was a 1-W metal halide lamp (Sylvania Metalarc, Osram Sylvania, Danvers, Massachusetts, USA) providing a PPFD of up to 1 µmol m s 1. For the determination of the CO compensation point (Γ), the linear portion of the A C I curves was extrapolated to the abscissa by linear regression analysis. The relationship of both Γ* and R d to leaf age (LPI) and phenological stage was determined with the laboratory gas-exchange system at 7.1 C leaf temperature according to Brooks and Farquhar (198). No consistent differences in the size of sun and shade leaves were found, nor evidence for photoinhibition of shade leaves exposed to high light during the measurements, as judged from the stability of A during extended periods under these conditions. Field gas-exchange measurements Gas exchange was measured with a modified open-system gasexchange apparatus (ADC-LCA, Hoddesdon, UK) during several of the six phenological phases in France. Measurements were conducted between 9 and 1 hours on days with PFD >1 µmol m s 1, high leaf temperatures (> C), and non-limiting vapour pressure deficit. A C i response curves were generated by connecting a high CO source to the gas-exchange apparatus and recording the draw-down in external CO concentration concomitant to the changes in photosynthetic behaviour of the leaves. In general, leaf temperature during this time (approximately min) varied by C. The resulting curves were very similar to A C i curves performed in the laboratory at comparable temperatures. During all measurements natural light was used. For measurements on shade leaves, shoots growing inside the canopy were temporarily exposed to full sunlight. The PPFD impinging on the leaf surface was measured parallel to the measurements of leaf gas exchange with a quantum sensor. In Germany, leaf gas exchange was measured with a portable open gas-exchange system (CO /H O porometer, Walz, Effeltrich, Germany). The light response of A was determined by first exposing the leaves to full light intensity, then lowering PPFD progressively with transmission filters (Schott, Mainz, Germany) to complete darkness. The time the leaves needed to reach a new steady state after each change of PPFD was between and 8 min. When the ambient temperature was very high (> C), leaf temperature typically decreased by C after leaves were submitted to darkness. At cooler air temperatures, the variation in leaf temperature was only 1 C or less. After being exposed to darkness for about 1 1 min, night (i.e. dark) respiration (R n ) was recorded. Measurements were conducted at low leaf-to-air vapour pressure deficits to avoid negative effects of low humidity on A. Most of these measurements were conducted during phenological phases II and III. Some diurnal measurements of photosynthesis in sun and shade leaves of different LPI were conducted throughout the season. Results Model parameterisation All model parameters were estimated separately for sun and shade leaves. The relationships of Γ, Γ*, R n and R d to leaf age (LPI) were pooled over the first four phenological phases. Despite a strong increase in Γ for young leaves below a LPI of approximately, there was no difference between leaf type (sun and shade) (Fig. 1A) and there was no age response in the absence of mitochondrial respiration (Γ*, Fig. 1B). The results for R d to LPI showed a strong increase in R d for leaves younger than LPI 1 (Fig. 1D). The rate of R d for sun leaves was about. µmol m s 1 higher than that for shade leaves irrespective of LPI (Fig. 1D). The values of R d were only about a third of dark respiration, R n, and overall relatively low (Figs 1C, D). Over the course of most of the season, R d of sun leaves with LPI > 1 varied little at a given temperature but R d of shade leaves decreased. Near the period around harvest (PP VI), R d attained the lowest values and there were no more differences between sun and shade leaves detectable (Fig. A). No response of Γ* to time was seen during the season, nor any differences between sun and shade leaves (Fig. B). For the model it was assumed that the basic relationships between R d and LPI, and Γ* and LPI shown in Fig. 1, did not change during the season. After the determination of R d, V cmax was estimated by fitting the model to measured A C i data under saturating light for C i < Pa ( data points), because it can be assumed that V C is limited only by W c in this range. Finally, J max and TPU were estimated by fitting the model, with previously estimated V cmax and R d, to the complete A C i

5 A model of limitations on leaf photosynthesis Functional Plant Biology 77 curves by least-squares non-linear regression analyses with the program PROC NLIN of SAS (SAS Institute, Cary, North Carolina, USA, 1987). In Fig., a representative set of A C i curves of sun and shade leaves of different LPIs during the six phenological phases is shown. There are no shade effects on photosynthetic responses to C i before bloom (PP II) when canopy development is not complete. Starting with PP II, photosynthetic capacity started to show differences between sun and shade leaves (Figs B, H). The differences between growing (LPI < 1) and mature (LPI >1) leaves were smaller for shade than for sun leaves (Figs I L cf. C F). Strong aging effects were apparent for leaves with LPI > from PP IV until harvest (Figs D F, J L). During the late phases of the season, the overall shape of the A C i curves became much flatter irrespective of LPI (Figs E F, K L), indicating substantial changes in V cmax, J max and TPU (Fig. ). Figure shows an example of these changes for two leaf age classes, LPI 1 (mature leaves) and LPI 8 (developing leaves). Only minor changes were apparent for the first four phenological phases (up to 1 week after veraison, beginning of fruit maturity) for mature leaves of both sun and shade types in V cmax, J max and TPU (Figs A C). For sun leaves, all three parameters decreased by about % in PP VI as compared with mid-season PP III. For mature shade leaves, the reduction was only about % over the same period (Figs A C). It seemed that the behaviour of the younger leaf age class was different. For sun-type leaves, there was a gradual but small decrease in all three parameters over the course of the season. For example, J max decreased from about 1 µmol m s 1 in PP I to about µmol m s 1 on average in PP VI, indicating a much smaller reduction in RuBP regeneration capacity as compared with older leaves (Fig. B). For shade leaves of the same age class, J max continuously decreased from about 8 to 7 µmol m s 1 on average over the same period (Fig. B), indicating that increasingly shaded conditions through continuous canopy development strongly affected developing leaves later in the season. The developmental changes in V cmax and TPU were similar and all three parameters remained highly coordinated throughout the season (Figs A C). This is also evident from a plot of J max versus V cmax over all leaf ages at a temperature of 7.1 C for the beginning and the end of the season (Fig. ). The slope increased slightly with time, but was not significantly different (strong overlap of the 9% confidence intervals). Shade leaves responded similarly to sun leaves (Fig. ). Γ (Pa) 1 1 A Primary Secondary Old Young Sun Shade Γ * (Pa) 8 B R n (µmol m s 1 ) 1 C (µmol m s 1 ) R d.8... D 1 1 LPI. 1 1 Fig. 1. Dependence of (A) Γ, (B) Γ*, (C) R n and (D) R d on LPI for sun and shade leaves. Values are shown for leaves on primary and lateral (secondary) shoots [young (apical) and old (basal)]. Values for secondary shoots represent the mean ± s.e. of leaves. Measurements were conducted during PP II and III at 7.1 ±. C according to Brooks and Farquhar (198) on potted plants. Lines are non-linear regression estimates based on eqns 8 and 9 with the parameters for Γ vs LPI (A) taken from Schultz et al. (199). For Γ* vs LPI (B): Γ* = LPI (r <.1). For R n vs LPI (C): sun, R n =.177e.LPI +. (r =.9); shade, R n =.881e.1LPI +.99 (r =.9). For R d vs LPI (D): sun, R d =.78e.111LPI +.18 (r =.9); shade, R d =.e.9lpi +.17 (r =.9). LPI

6 78 Functional Plant Biology H. R. Schultz The temperature responses of V cmax, J max and TPU were evaluated from A C i curves conducted on leaves of LPI > 1 during PP I IV. Most of the data obtained were from laboratory experiments, but some A C i curves conducted in the field at high temperatures (> C) were added. While fitting eqn 7 to the data, the energy deactivation term H d was fixed at kj mol 1, similar to the examples presented by Harley et al. (199) and Harley and Baldocchi (199) to achieve adequate parameter estimates and to meet the convergence criteria of the non-linear regression procedure. All parameter values are given in Table 1. The temperature optimum for V cmax was higher than for J max, irrespective of the leaf type, but resided at higher levels for sun than for shade leaves (Figs A, B). The response of TPU to leaf temperature followed a pattern similar to that for J max for both sun and shade leaves, and strongly decreased at temperatures > C (Figs B, C). When plotting the ratio of J max to V cmax of all data points as a function of leaf temperature, a decrease with increasing temperature was apparent for both leaf types (Fig. 7A). This R d (µmol m s 1 ) Γ* (Pa) A B Sun Shade I II III IV V VI Phenologic phase Fig.. Seasonal changes in R d (A) and Γ* (B) for sun and shade leaves of age LPI > 1 of primary shoots of potted plants estimated at a measurement temperature of 7.1 ±. C. In B, symbols for sun and shade leaves are alternating because values for both treatments could not be distinguished from each other for any phenological phase. Phenological phases are also presented in picture code according to the developmental scale of Eichhorn and Lorenz (1977). again indicated a highly coordinated relationship between Rubisco activity and/or kinetic properties and RuBP regeneration capacity over the entire range of temperatures encountered. The relative stability of this ratio could also be demonstrated for sun and shade leaves varying in age at a temperature of 7.1 C (Fig. 7B). The ratio J max /V cmax could be used in modelling seasonal dynamics in photosynthesis of canopies with large differences in leaf age populations, assuming that it follows the same temperature dependence for all leaf ages of sun and shade leaves and that the ratio remains constant throughout the season (as was the case) even though the absolute values of V cmax and J max may change (compare Figs and ). In order to describe the light response of sun and shade photosynthesis, data for α from the literature were used first (e.g. Harley and Baldocchi 199) to fit eqn. The known estimates of α, however, are sometimes the result of experiments conducted at saturating CO concentrations (Harley and Tenhunen 1991; Wohlfahrt et al. 1999), based on quantum use efficiency data from the literature (Ehleringer and Björkman 1977; Harley et al. 199), or estimated from light response curves at ambient CO concentrations over a narrow temperature range (Harley and Baldocchi 199), all yielding very different values. For these reasons, light response curves of photosynthesis were conducted in the field at different temperatures and subsequently analysed to obtain reasonable values for α to be incorporated into the model (Fig. 8). Using the previously estimated parameters for V cmax, J max and TPU as a function of temperature, α was estimated for leaves of LPI > 1. Figure 8 shows that the shape of the light response curves changed substantially with increasing temperature and that an adequate fit of the model equations could only be obtained by adjusting the values of α accordingly. The stomatal conductance model states that multiplying A, measured at different light intensities, relative humidity, temperatures and CO concentration, with a factor consisting of the relative humidity (h) divided by C a, would yield a linear relationship with the simultaneously measured g s (Ball et al. 1987). That this relationship holds for sun and shade grapevine leaves of different LPIs measured at different temperatures, humidities and light intensities during the course of several days in the field is shown in Fig. 9. The resulting relationship between g s and A(h/C a ) is linear and not significantly different between sun and shade leaves. The completely parameterised model was then tested on three independent data sets from diurnal measurements of photosynthesis and stomatal conductance of sun and shade leaves of different leaf age classes under natural conditions. Driving variables were measured values of PPFD, leaf temperature, h and C a. The resulting simulations were compared with measured g s and A for three days during different phenological phases in June, July and October, each time for a different age class (Fig. 1). The leaf

7 A model of limitations on leaf photosynthesis Functional Plant Biology 79 temperature spectrum covered was from > C for the day in July down to. C for early-morning conditions in October (Fig. 1). The PPFD varied from overcast conditions for the day in June to very high PPFD values for the day in July. Despite some overestimation of g s during the day in July, the model effectively simulated A and g s and closely traced the time course of measured values for both sun and shade leaves of different ages. Discussion Model parameterisation On the basis of a large data set of A C i curves (n=1), the dependence of CO assimilation on PPFD, temperature, leaf age and time during the season was described for individual grapevine leaves previously exposed to different light environments using the Farquhar model (Farquhar et al. 198). The approach used here differed somewhat from most other model parameterisations (e.g. Harley and Baldocchi 199; Maroco et al. ) in that R d and Γ* were estimated separately first and then used as fixed values in the non-linear regression analyses (Sims and Pearcy 1989). The values found for R d of grapevine leaves were lower (about. µmol m s 1 for sun leaves and.18 µmol m s 1 for shade leaves at 7 C) than those reported for most other studies, including work on Eucalyptus (Kirschbaum and Farquhar 198), Alocasia (Sims and Pearcy 1989), cotton (Harley et al. 199), oak and maple (Harley and Baldocchi 199) and more recently on walnut (Frak et al. 1) and other cultivars of grapes than those used in the present study (Escalona et al. 1999; Maroco et al. ). In most cases these R d values were estimated from A C i curves, whereas the values presented here were estimated according to Brooks and Farquhar (198). The ratio of R d /R n was about. for fully grown leaves, which is similar to that reported by Brooks and Farquhar (198) but only about half the. determined by Kirschbaum and Farquhar (198). This ratio, however, seems to be quite variable and can even approach unity depending on the light environment in which these leaves developed (Sims and Pearcy 1989). Sims and Pearcy (1989) and Frak et al. (1) found an increase in R d with light intensity, whereas Harley and Baldocchi (199) parameterised the inverse. Also in some models, no response of R d to temperature is included (Harley et al. 199), whereas a positive response is usually assumed (Kirschbaum and Farquhar 198). Peisker et al. (1981) A (µmol CO m s 1 ) A G 1 Sun Shade B H 1 1 C I 1 1 D J 1 1 E K 1 1 F L C i (Pa) Fig.. CO -response curves for sun (A F) and shade leaves (H L) of different LPIs on primary shoots during the course of the season. Numbers near curves indicate LPI. Measurements were conducted at 7.1 ±. C. Symbols represent measured values, lines are fitted using eqns 1, 8 and 9. The picture code represents phenological phases (see Fig. ).

8 8 Functional Plant Biology H. R. Schultz found that the ratio of R d /R n averaged about. but varied during ontogenetic development between. and.8. Since R d can also increase with an increase in leaf J max (µmol m s 1 ) V cmax (µmol m s 1 ) A B carbohydrate level (Azcon-Bieto and Osmond 198), changes as a response to altered source sink relationships during the season may be expected, yet were not observed in the present study. Estimates of Γ* for different LPIs and times during the season showed no response to leaf age and phenological stage. This is expected, since Γ* depends only on O and on the ratio of kinetic constants associated with carboxylation and oxygenation, which does not appear to change with age (Azcón-Bieto et al. 1981). For the estimates of V cmax, J max and TPU, a two-step analysis was used, first to estimate V cmax from A C i relationships up to Pa, and then fitting the full model to the entire curve. At low C i and high values of PPFD, RuBP is present in excess and photosynthesis is limited by the kinetic properties of Rubisco, determined by the value of V cmax (Farquhar and von Caemmerer 198). RuBP regeneration determined by J max becomes limiting only at lower PPFDs and/or higher temperatures and C i values. Since all A C i measurements were conducted at high PPFD (> 1 µmol m s 1 ), and C i values reached about 1 Pa at the most (see Fig. ), there was no co-limitation by V cmax and J max, and RuBP regeneration became limiting only at the highest calculated C i values. The estimation of J max was therefore sometimes difficult, and, similar to the study by Harley and Baldocchi (199), estimates here should be taken as minimum. The third parameter, TPU, becomes 8 C 1 TPU (µmol m s 1 ) Sun, LPI 1 Shade, LPI 1 Sun, LPI 8 Shade, LPI 8 I II III IV V VI Phenologic phase Fig.. Estimated values of (A) V cmax, (B) J max and (C) TPU from A C i curves for sun and shade leaves of different LPI classes during the course of the season. Measurements were conducted at 7.1 ±. C. Data are means ± s.e. from two or three leaves per class and phenological phase. Curves are second- or third-order polynomial regressions to show seasonal development. Results from regression analyses for age class LPI 1 are as follows. For V cmax (A): sun, V cmax = PP.PP +.9PP (r =.98); shade, V cmax =. +.9PP 1.7PP +.91PP (r =.79). For J max (B): sun, J max = PP 1.7PP.7PP (r =.9); shade, J max = PP + 7.9PP.PP (r =.7). For TPU (C): sun, TPU = 8.9.PP +.8PP.8PP (r =.98); shade, TPU =. + 1.PP.1PP (r =.7). J max (µmol m s 1 ) 1 Sun, PP V VI Sun, PP I II Shade, PP V VI Shade, PP II 8 V cmax (µmol m s 1 ) Fig.. Relationship between J max and V cmax of sun and shade leaves at 7.1 ±. C. Data were separated into two date groups: PP I and II (beginning of the season) and PP V VI (end of the season). Regression equations were: J max =. +.V cmax (solid line, r =.91) in PP I II; J max =. +.1V cmax (dashed line, r =.8) in PP V VI. Slopes were not significantly different (at 9% confidence intervals) from each other.

9 A model of limitations on leaf photosynthesis Functional Plant Biology 81 rarely limiting at all, is difficult to estimate if A C i responses do not become completely flat at high C i levels, and is ignored in the parameterisation of many models. Estimating TPU values in this study sometimes required many runs of the fitting routine before convergence criteria were met. The values of both J max and TPU nevertheless still compare well with those estimated for this species in other studies (Maroco et al. ). Thomas and Strain (1991) have shown for cotton that low values in J max and V cmax can be the result of using potted plants. Plants chosen for the present study had photosynthetic activities at ambient CO concentration that were comparable to those encountered in the field, and thus artefacts introduced by root restriction can be excluded. To obtain an adequate fit for the light response curves measured at ambient CO concentration and different J max (µmol m s 1 ) V cmax (µmol m s 1 ) TPU (µmol m s 1 ) A B C Sun Shade 8 8 Leaf temperature ( C) Fig.. Estimates of V cmax, J max and TPU, for sun and shade leaves of plants grown in pots and in the field, plotted as a function of leaf temperature. Curves are non-linear least-squares fits to eqn 7 for leaves of LPI > 1 during PP II IV (r >.78 in all cases). temperatures, α needed to be adjusted (Fig. 8; Table 1). In modelling studies, α is determined in quite different ways. Sims and Pearcy (1989), Harley and Tenhunen (1991) and Wohlfahrt et al. (1999) measured α at saturating CO concentrations, whereas Harley and Baldocchi (199) did so at ambient CO concentration, and others use values of quantum use efficiency from the literature (Harley et al. 199; Wilson et al. 1 based on Ehleringer and Björkman 1977). The most common value used in the cited studies is. (mol electrons per mol photons) for sun leaves at about C and. for shade leaves over the same temperature range. This agrees reasonably well with the estimated α values over the range 1 C in the present study (Fig. 8). The values also agree well with those previously estimated for grapevines and kiwifruit from fluorescence and gasexchange measurements (Iacono and Sommer ; Greer and Halligan 1). In addition, Iacono and Sommer () found no differences in α between different LPIs for grapevines. Quantum yield should be sensitive to high temperatures (Ehleringer and Björkman 1977), and similar to the observations made here, has been found to decrease J max /V cmax J max /V cmax 1 Sun Shade 8 8 Leaf temperature ( C) LPI Fig. 7. Relationship of the ratio of J max /V cmax as a function of leaf temperature for sun and shade leaves of age LPI > 1 during PP II IV (A), and as a function of LPI (B) at a constant leaf temperature of 7.1 ±. C. Data for A are from Fig.. Regression equations were: for A, J max /V cmax = 1.1.T +.T (r =.78); and, for B, J max /V cmax = LPI (r =.1). A B

10 8 Functional Plant Biology H. R. Schultz Net photosynthesis (µmol m s 1 ) 1 1 A 1 C B C C C D C E > C Sun Shade α(sun) =. α(shade) =. α(sun) =.19 α(shade) =. α(sun) =.19 α(shade) =. α(sun) =.1 α(shade) =.1 α(sun) =.1 α(shade) = PPFD (µmol m s 1 ) Fig. 8. Relationship between measured (symbols) and simulated (lines) net photosynthesis and incident PPFD for sun and shade leaves of LPI > 1 at different temperatures (A E) measured at ambient CO concentration in the field. Measurements were performed during PP II IV over years ( ). Simulations were done with parameters estimated by eqns 11 for the appropriate temperatures (always for the average of the given temperature range) and by eqn using different values for α. The figure insets show the estimated values for α resulting in the curves shown. substantially above C in another field study with grapes (Jacobs et al. 199). However, in an earlier modelling study with soybean, α was found to be insensitive to leaf temperature above C (Harley et al. 198). Changes in quantum use efficiency could also be related to photoinhibition, which may be exacerbated at high temperatures. These factors have recently been incorporated into a canopy photosynthesis model (Werner et al. 1). Whether photoinhibition played a role during measurements of the PPFD response curves is unknown, but it seems important to let α vary with temperature to apply the model to grapevines grown under a wide range of climatic conditions (Schultz et al. 1). The temperature dependence of V cmax, J max and TPU was estimated according to the equation proposed by Harley and Tenhunen (1991) and Harley et al. (199). It was difficult to fit eqn 7 to the data, especially for shade leaves, since values for high temperatures were lacking. Harley and Baldocchi (199) and Wohlfahrt et al. (1999) used slightly altered versions of this equation, which may improve curve-fitting results but has recently been shown to overestimate Rubisco-limited photosynthesis at high leaf temperatures (Bernacchi et al. 1). Nevertheless, the parameters estimated here adequately predicted the effects of leaf temperature on both photosynthesis and stomatal conductance for diurnal time courses over a large temperature range (. C in October to. C in July). Although there is much concern whether there is any mechanistic ground for the Ball Woodrow Berry model (Ball et al. 1987) of stomatal conductance (Leuning 199; Aphalo and Jarvis 199; Monteith 199), for several species good linear correlations have been obtained from various leaf gas-exchange experiments (Leuning 199; Harley and Baldocchi 199; Lloyd et al. 199; Schultz et al. 1999). These correlations equally hold for sun and shade leaves (Harley and Baldocchi 199; Sala and Tenhunen 199). The parameterisation of the model for grapevines was based on g s (mmol m s 1 ) 1 Sun Shade A(h /C a ) Fig. 9. Relationship between stomatal conductance to water vapour and the factor A(h/C a ) for sun and shade leaves of different LPIs during PP II and III. Data are for Riesling plants during July and August, and were collected in the field at an ambient C a of Pa with different temperatures, humidities and PPFD values. The solid line is a linear fit to all measured data (sun and shade) from the following equation: g s = A(h/C a ) (r =.7).

11 A model of limitations on leaf photosynthesis Functional Plant Biology 8 diurnal measurements with different leaf types, varying light intensities (1 17 µmol m s 1 PPFD), large fluctuations in temperature (1 C) and humidity ( 7%). As a result, the model effectively described the complex interactive effects of PPFD and temperature, mediated through humidity, on conductance at ambient C a similar to examples with other species (Harley and Tenhunen 1991; Harley and Baldocchi 199; Lloyd et al. 199). Recently, Katul et al. () successfully modelled changes in C i /C a, which is related to k in the Ball Woodrow Berry model, as a function of stomatal conductance for several species, grapevines included, on the basis of data in the literature. Effects of leaf age, leaf type (sun, shade) and time during the season The differences in parameter values between sun and shade leaves are consistent with the general trends reported for sun versus shade ecotypes (Sims and Pearcy 1989), including lower rates of PPFD-saturated photosynthesis and higher quantum use efficiencies for shade leaves. The shadeinduced reduction in photosynthetic capacity was evident in decreases of V cmax, J max and R d. At a temperature of 7 C, all three parameters were about % lower at mid-season, which is similar to results obtained in shade-acclimation experiments with walnut (Frak et al. 1). The reduction A (µmol m s 1 ) g s (mmol m s 1 ) Leaf temperature ( C) PPFD (µmol m s 1 ) A LPI 1 June B LPI 1 July C LPI Sun Shade D E F G H I J K L October Sun, measured Sun, simulated Shade, measured Shade, simulated Time (h) Fig. 1. The diurnal pattern of g s (G I) and A (J L) measured for sun and shade leaves of different age classes on three different dates ( June, 11 July, October) during the season. Lines are model simulations based on parameters estimated by eqns 1 1. Symbols are measured values. Measured values of PPFD and leaf temperature used to drive the simulations are also shown (A F).

12 8 Functional Plant Biology H. R. Schultz observed in the TPU in shade leaves, leading to a diminished supply of inorganic phosphate (P i ) to the Calvin cycle, is consistent with the slow-down in growth generally observed for shaded plants (Sims and Pearcy 1989). Leaf age influences the acclimation process to low light, with fully developed leaves requiring longer periods than growing leaves (Jurik et al. 1979; Frak et al. 1). Integrating these processes into canopy models has been attempted (Niinemets and Tenhunen 1997; Kull and Kruijt 1999), but the processes are difficult to quantify for all developmental stages. The differences in V cmax, J max and R d between sun and shade leaves decreased at the end of the season, which may be related to differences between sun and shade leaves in nitrogen re-translocation (Frak et al. 1), which is important for grapevine photosynthesis in this phase (Williams and Smith 198). The J max /V cmax ratio provides an estimate of the relative activities of RuBP regeneration and carboxylation capacities in a leaf. The response to light environment of this ratio is not clear. In some cases increasing ratios with increasing growth PPFD were reported (Ferrar and Osmond 198; Evans 1987) in others, decreasing or unaltered ratios were found (von Caemmerer and Farquhar 1981; Sims and Pearcy 1989). Sage (199) postulated that RuBP regeneration capacity and Rubisco activity are controlled so that when one is limiting the other is downregulated, thus the ratio of J max to V cmax would remain approximately constant. The data presented here fully support this, since at a given temperature neither leaf age nor light environment had an influence on J max /V cmax. Despite similar ratios between sun and shade leaves of different LPIs at a given time during a season, this ratio has been reported to increase during the season for several tree species (Wilson et al. a). With grapevines, only a small, not significant shift to higher ratios at the end of the season (PP V VI) was observed, indicating a large degree of stability between activity and/or amount of Rubisco and RuBP regeneration capacity, despite presumably large changes in foliar nitrogen concentration over time (Williams and Smith 198). The increase in the ratio of J max /V cmax reported by Wilson et al. (a) could be partly due to drought, whereas in the present study drought effects have been avoided. In general the ratios of J max /V cmax reported here were between. and.1, and thus close to the values obtained by Maroco et al. () in a study on drought effects on grapevines (. for well-watered plants,. for stressed plants), and Wullschleger (199) (..), who recalculated data from the literature. The temperature dependence of V cmax, J max and TPU was determined for the summer part of the season (PP II IV). Acclimation to high or low temperatures may occur in leaves (Berry and Björkman 198). The simulation results for the cool day in October (morning leaf temperature of. C), however, showed no substantial offset between measured and simulated photosynthetic rates. Since the properties of Rubisco do not acclimate (Berry and Björkman 198) and R d, which has been shown to acclimate to temperature (Azcón-Bieto et al. 1981), remained at very low levels (Fig. ), any important temperature acclimation must have been related to photosynthetic electron transport (Berry and Björkman 198). Niinemets et al. (1999) showed a strong modification of the temperature response of photosynthetic electron transport in trees through differences in light climate. They also showed that R d responded to long-term canopy light and temperature environment. At present it is unclear whether these modifications are of any importance for the application of the model for grapevines. Temperature optima for V cmax, J max and TPU differed from each other in the present study. In both sun and shade leaves, V cmax had a higher temperature optimum than J max and TPU. This could be related to the difference in temperature sensitivity of RuBP regeneration (high) as compared with the initial slope of the A C i curve (low) (Kirschbaum and Farquhar 198), which does affect the ratio of J max to V cmax (Fig. 7). Wohlfahrt et al. (1999) evaluated the temperature response of 9 species from differently managed mountain grassland ecosystems, and in 1 cases found a slightly higher temperature optimum for V cmax than for J max (mean.1 C, maximum. C). Leaf age effects under well-watered conditions were primarily indicated through diminished photosynthetic capacity (V cmax ) and not stomatal closure in this and other studies with grapevines (Schultz et al. 199; Escalona et al. 1999) or trees (Niinemets ). This interpretation is subject to the assumption that the extent of patchy stomatal closure and mesophyll resistance does not increase substantially during the season and lead to erroneous estimates of C i. Under the conditions of the gas-exchange measurements, in the absence of water deficit, errors in C i calculation due to stomatal patchiness are less likely to occur (Mott and Buckley ). An adequate description of the seasonal dynamics in V cmax and J max is important for future incorporation of these parameters into whole canopy models. For example, removing the temporal trends in simulations of the net ecosystem exchange of carbon in a deciduous forest by using the early maximum in V cmax over the entire season overestimated the annual carbon uptake by about % (Wilson et al. 1). Even the use of a seasonal mean value led to large errors. Harley et al. (199) also found a significant effect of plant age on all photosynthetic parameters, with substantial decreases over time. V cmax and J max are usually tightly coupled to nitrogen concentration in the leaves, which can integrate the effects of differences in the light environment during growth (Sims and Pearcy 1989). In white oak and red maple, for example, large differences in V cmax, J max and TPU were apparent between sun and shade leaves on a per-unit-leaf-area basis. When these parameters were expressed on a per-unit-dry-

13 A model of limitations on leaf photosynthesis Functional Plant Biology 8 weight or per-unit-nitrogen basis, the differences were almost eliminated (Harley and Baldocchi 199). Differences in nitrogen content may be the reason why lateral leaves on grapevine shoots have superior rates of CO gas exchange at the end of the growing season (Palliotti et al. ). However, the relationship of V cmax and J max to leaf nitrogen concentration also undergoes seasonal trends and may become decoupled at times (Wilson et al. 1). Grapevines undergo continuous shifts in source sink relationships throughout the season. These shifts can influence carbohydrate storage in the leaves through limitation in sink strength at certain periods during the season (Chaumont et al. 199; Hunter et al. 199). Under these conditions, which may limit the ability to sustain high chloroplast levels of P i, an imbalance between triose-phosphate production and utilisation can occur, which could become limiting for A (Herold 198). One cannot exclude this possibility but under the experimental conditions used, TPU was not limiting at ambient CO and was of no importance for the simulations. Conclusion This study describes the parameterisation of a mechanistic model of photosynthesis (Farquhar et al. 198) for grapevines to include effects of light environment, phenology and leaf age in the absence of water deficit. By coupling this model to the stomatal conductance model of Ball et al. (1987), diurnal variations in leaf photosynthesis and stomatal conductance could be simulated for a wide range of environmental conditions, leaf ages and phenological phases. The model provides a platform to incorporate aspects of plant water relations and plant nutritional status in the future, and could be scaled up to estimate the photosynthetic performance and water consumption of whole grapevine canopies. Apart from the role in light interception, CO acquisition and water loss, canopy structure mediates whole-plant responses to environmental stresses such as water deficit or high light (or both) (Tenhunen et al. 199; Werner et al. 1). Since many different grapevine varieties are grown over a large climatic transect from cool temperate through the dry Mediterranean-type climates to the tropics, and in a multitude of different canopy systems, grapevines are an ideal tool to address the problem of modelling whole plant (vineyard) gas exchange. However, this variability will require considerable further study on model parameters to be included. Acknowledgments I am very grateful to Prof. Robert Pearcy (University of California, Davis) for letting me use his gas-exchange system and to Prof. João Maroco (Instituto de Tecnologia Quimica et Biológica, , Oeiras, Portugal) for providing me with a spreadsheet that made the control of model parameter estimates so much easier. This research was funded over the years by the Deutsche Forschungsgemeinschaft and the European Community (FAIR-17). Additional experimental work was done at the Department of Botany, University of California, Davis, USA, and at INRA/ENSA, UFR Viticulture, Montpellier, France. References Amthor JS, Goulden ML, Munger JW, Wofsy SC (199) Testing a mechanistic model of forest-canopy mass and energy exchange using eddy correlation: carbon dioxide and ozone uptake by a mixed oak maple stand. Australian Journal of Plant Physiology 1, 1. Aphalo PJ, Jarvis PG (199) An analysis of Ball s empirical model of stomatal conductance. Annals of Botany 7, 1 7. Azcón-Bieto J, Osmond CB (198) Relationship between photosynthesis and respiration. The effect of carbohydrate status on the rate of CO production by respiration in darkened and illuminated wheat leaves. Plant Physiology 71, Azcón-Bieto J, Farquhar GD, Caballero A (1981) Effects of temperature, oxygen concentration, leaf age and seasonal variations on the CO compensation point of Lolium perenne L. Planta 1, 97. Baldocchi DD, Harley PC (199) Scaling carbon dioxide and water vapour exchange from leaf to canopy in a deciduous forest. II. Model testing and application. Plant, Cell and Environment 18, Ball JT, Woodrow IE, Berry JA (1987) A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. In Progress in photosynthesis research. Vol IV. Proceedings of the VII international congress on photosynthesis. (Ed. I Beggins) pp. 1. (Martinus Nijhoff: Dordrecht). Bernacchi CJ, Singsaas EL, Pimentel C, Portis AR, Long SP (1) Improved temperature response functions for models of Rubiscolimited photosynthesis. Plant, Cell and Environment, 9. Berry JA, Björkman O (198) Photosynthetic response and adaptation to temperature in higher plants. Annual Review of Plant Physiology 1, 91. Bond BJ () (Ed.) Aging in pacific northwest forests. Tree Physiology (/, Special issue). Brooks A, Farquhar GD (198) Effect of temperature on the CO /O specificity of ribulose-1,-bisphosphate carboxylase/oxygenase and the rate of respiration in the light: estimates from gas-exchange experiments on spinach. Planta 1, 97. Caldwell MM, Meister HP, Tenhunen JD, Lange OL (198) Canopy structure, light microclimate and leaf gas exchange of Quercus coccifera L. in a Portuguese macchia: measurements in different canopy layers and simulations with a canopy model. Trees 1, 1. Cartechini A, Palliotti A (199) Effect of shading on vine morphology and productivity and leaf gas exchange characteristics of grapevines in the field. American Journal of Enology and Viticulture, 7. Chaumont M, Morot-Gaudry J-F, Foyer CH (199) Seasonal and diurnal changes in photosynthesis and carbon partitioning in Vitis vinifera leaves in vines with and without fruit. Journal of Experimental Botany, 1 1. Day W, Parkinson KJ (198) Application to wheat and barley of two leaf photosynthesis models for C plants. Plant, Cell and Environment, 1 7. Dokoozlian NK, Kliewer WM (199) The light environment within grapevine canopies. II. Influence of leaf area density on fruit zone light environment and some canopy assessment parameters. American Journal of Enology and Viticulture, 9.