Tree Physiology 22, 929–938 © 2002 Heron Publishing—Victoria, Canada

Effects of crown development on leaf irradiance, leaf morphology and photosynthetic capacity in a peach tree ADRIAN WALCROFT,1–3 XAVIER LE ROUX,1,4 ANTONIO DIAZ-ESPEJO,5,6 NICOLAS DONES1 and HERVÉ SINOQUET1 1

UMR PIAF, INRA-Université Blaise Pascal, Domaine de Crouelle, 234 av. du Brezet, 63039 Clermont-Ferrand Cedex 2, France

2

Present address: Landcare Research, Private Bag 11052, Palmerston North, New Zealand

3

Author to whom correspondence should be addressed ([email protected])

4

Present address: Laboratoire d’Ecologie Microbienne (UMR 5557 CNRS-Université Lyon I), bat 741, 43 bd du 11 novembre 1918, 69622 Villeurbanne, France

5

IRNASE, Campus de Reina Mercedes, Apdo. 1052, 41080, Seville, Spain

6

Present address: Dept. Soil Science, Reading University, Whiteknights, P.O. Box 233, Reading RG6 6DW, U.K.

Received December 7, 2001; accepted May 5, 2002; published online August 1, 2002

Summary The three-dimensional (3-D) architecture of a peach tree (Prunus persica L. Batsch) growing in an orchard near Avignon, France, was digitized in April 1999 and again four weeks later in May 1999 to quantify increases in leaf area and crown volume as shoots developed. A 3-D model of radiation transfer was used to determine effects of changes in leaf area density and canopy volume on the spatial distribution of absorbed quantum irradiance (PAR a). Effects of changes in PAR a on leaf morphological and physiological properties were determined. Leaf mass per unit area (Ma) and leaf nitrogen concentration per unit leaf area (Na) were both nonlinearly related to PAR a, and there was a weak linear relationship between leaf nitrogen concentration per unit leaf mass (Nm) and PARa. Photosynthetic capacity, defined as maximal rates of ribulose-1,5-bisphosphate carboxylase (Rubisco) carboxylation (Vcmax) and electron transport (Jmax), was measured on leaf samples representing sunlit and shaded micro-environments at the same time that the tree crown was digitized. Both Vcmax and Jmax were linearly related to Na during May, but not in April when the range of Na was low. Photosynthetic capacity per unit Na appeared to decline between April and May. Variability in leaf nitrogen partitioning between Rubisco carboxylation and electron transport was small, and the partitioning coefficients were unrelated to Na. Spatial variability in photosynthetic capacity resulted from acclimation to varying PAR a as the crown developed, and acclimation was driven principally by changes in Ma rather than the amount or partitioning of leaf nitrogen. Keywords: carboxylation rate, electron transport rate, leaf mass per unit area, nitrogen, photosynthesis, photosynthetic temperature response, Prunus persica.

Introduction In deciduous trees, the spatial distribution of solar radiation within the crown alters as crown architecture changes with shoot and foliage development. In species where vegetative shoot growth is determinate, such as sugar maple (Acer saccharum Marsh; Canham et al. 1999), most of the architectural development occurs early in the growing season. The effect of crown architecture on the radiation micro-environment therefore remains largely invariant once shoot growth and leaf expansion are complete. However, in species such as peach (Prunus persica L. Batsch), where vegetative shoot growth is indeterminate, shoot elongation and leaf expansion continue to affect the radiation micro-environment throughout the growing season (Grossman and DeJong 1994). Leaves that develop in a particular light environment must often acclimate to a different light environment, and new leaves may develop in quite different light environments depending on their spatial location within the tree crown. Leaf development in, or acclimation to, different light environments may be driven by changes in leaf structural mass and nitrogen concentration (Niinemets and Tenhunen 1997, Le Roux et al. 1999a, Rosati et al. 1999, 2000, Warren and Adams 2001), or changes in the proportions of nitrogen allocated among different enzymes and processes within a leaf (Niinemets and Tenhunen 1997, Le Roux et al. 1999b, 2001, Evans and Poorter 2001, Frak et al. 2001), or both. In many species, it is apparent that acclimation to changing light results mainly from changes in leaf mass to area ratio (Ma), rather than changes in leaf nitrogen concentration per unit leaf mass (Nm) or nitrogen allocation (Niinemets et al. 1998, Rosati et al. 2000, Evans and Poorter 2001, Le Roux et al. 2001). This results in a change in the leaf nitrogen concentration per unit leaf area (Na, the product of Ma and Nm) that is almost invariably correlated with leaf photosynthetic capacity (defined as maxi-

930

WALCROFT, LE ROUX, DIAZ-ESPEJO, DONES AND SINOQUET

mal rates of ribulose-1,5-bisphosphate carboxylase (Rubisco) carboxylation (Vcmax) and electron transport (Jmax)). Thus, leaves in high-light environments have higher photosynthetic capacity than leaves in low-light environments, which leads to greater whole-tree photosynthesis compared with a uniform distribution of photosynthetic capacity (Leuning et al. 1995). This is the basis of the optimization hypothesis, and has been observed in many cases (e.g., Field 1983, Hirose and Werger 1987). This study formed part of a larger project to develop a model of carbon assimilation at the shoot scale, within the context of the whole tree, by scaling-up the Farquhar et al. (1982) model of leaf-level carbon assimilation using a 3-dimensional (3-D) model of radiation transfer. The high degree of correlation between photosynthetic capacity and leaf nitrogen concentration, and the ease with which leaf nitrogen concentration can be determined, means that leaf nitrogen concentration can be used to determine the spatial distribution of photosynthetic capacity when scaling carbon assimilation from the leaf-level to the whole tree. Temporal scaling of carbon assimilation requires, among other things, knowledge of the response of leaf-level photosynthetic parameters to temperature, because large temperature fluctuations occur throughout the growing season. However, the responses of parameters describing the component processes of photosynthesis, namely Vcmax and Jmax, have been quantified in relatively few species (Harley et al. 1992, Walcroft et al. 1997, Bernacchi et al. 2001, Dreyer et al. 2001, Medlyn et al. 2002b). In this paper, we describe the architectural development of a peach tree crown over a 4-week period, and document the effects of this development on absorbed quantum irradiance, and leaf morphological and photosynthetic characteristics. We quantified relationships between leaf photosynthetic capacity and nitrogen concentration twice during the fruit growth period, and determined the temperature dependencies of Vcmax, Jmax and dark respiration (Rd) in peach leaves. The specific objectives of the study were to (i) quantify the spatial variability of photosynthetic capacity within a peach tree crown, (ii) determine the relative contributions of changes in leaf mass and in nitrogen partitioning to light acclimation processes in peach leaves, and (iii) quantify the response of leaf photosynthetic capacity to temperature. Materials and methods Plant material Measurements were made during April and May 1999 on a 6-year-old peach tree at a site near Avignon, France (43.9° N, 4.8° E). The tree was of the early maturing variety “Alexandra,” and grew in an orchard at 5 × 5 m spacing on a silt-clay soil. The tree was goblet-pruned and subject to normal horticultural management practices with respect to fruit production, and was irrigated and fertilized to ensure non-limiting water and nutrient conditions. To quantify crown leaf area development during the season, tree crown architecture was measured twice, at an interval of

28 days, as described in detail by Sinoquet et al. (1997). Briefly, a 3-D digitizer (Fastrack, Polhemus, Colchester, VT) was used to record the spatial location of a pointer in relation to a fixed reference frame, with an accuracy of about 1 cm over a distance of up to 3 m. Beginning at the base of the tree, points were recorded at every branching junction, and at the ends of every leafy shoot, while also noting the location of all fruits. At the same time, tree topology was recorded as a multi-scale tree graph following Godin et al. (1999). This system allows the tree to be analyzed at a range of scales, and links components in terms of branching or succession. The tree was divided into components consisting of current-year vegetative shoots that bear foliage, 1-year-old shoots that bear fruit, and older woody shoots, noting branching and succession between individual shoots and branches. An allometric relationship between shoot length (Ll; m) and leaf area (La; m2) was determined on samples of 65–75 shoots from a range of crown positions on neighboring trees of the same cultivar. These data were combined with data from experiments in previous years on the same trees (F. Lescourret, unpublished data) to yield a single, linear relationship between L l and L a that adequately described the observed relationships at both sampling dates. The regression equation for shoots less than 0.75 m long (the maximum length observed) was: L a = 0.183L l + 0.0048 (r 2 = 0.90, n = 350). The positive y-intercept indicates the mean leaf area of spur shoots, which have a negligible length (< 0.05 m). Intra-crown radiation distribution Intra-crown distribution of absorbed photosynthetically active radiation (PAR a) was simulated with the 3-D model RATP (Sinoquet et al. 2001). In the model, the tree crown is represented by an array of 3-D cells (0.25 × 0.25 × 0.25 m). Leaf area is distributed among cells according to the spatial location and L a of individual leafy shoots. The L a of each leafy shoot was determined with the allometric relationship by first calculating the L l from the spatial coordinates of the shoot base and tip. The mean L a of spur shoots was applied to all shoots where L l was less than 0.05 m. The model calculates PAR a separately for sunlit and shaded leaves in each cell using the turbid medium analogy. An erectophile leaf angle distribution was assumed because this closely matches the measured leaf angle distribution in peach (Le Roux et al. 2001). Leaf reflectance and transmittance in the PAR waveband were both assumed to equal 0.085 throughout the canopy, resulting in a leaf absorbance of 0.83. For the near infrared (NIR) waveband, the coefficients for reflectance and transmittance were both assumed to equal 0.425. The radiation balance is solved for direct, diffuse and scattered (reflected and transmitted) radiation in the PAR and NIR wavebands to determine leaf irradiance in each cell. For more details on the radiation model see Sinoquet et al. (2001). Leaf sampling and gas exchange measurements Prior to tree digitizing at each site, leaves were identified from crown positions representing a range of sunlit through to

TREE PHYSIOLOGY VOLUME 22, 2002

CROWN DEVELOPMENT AND PHOTOSYNTHETIC CAPACITY IN PEACH

shaded shoots (n = 20). The spatial coordinates of each sample leaf were recorded so that the leaf could later be allocated to the appropriate 3-D cell. Mean irradiance for each sample leaf during the week before sampling was calculated by running the model on a 30-min time step using incident direct and diffuse global radiation measured within 10 m of the tree. Daily PAR a integrals were averaged to give a mean daily value of PAR a for foliage in each cell associated with a sample leaf over 1 week. Gas exchange measurements were made on a subset (n = 10–20) of the identified leaves after digitizing was completed to avoid interference between metal in the gas analyzer and the magnetic digitizer. Time constraints during April meant that tree digitizing and gas exchange measurements needed to be made concurrently, so the latter were made on a neighboring, clonal tree of similar dimensions and crop load located within 10 m of the digitized tree. Thus there was no possibility that genetic differences, and only a small possibility that environmental factors, would influence the results. The parameters of the photosynthesis model that describe photosynthetic capacity (Vcmax and Jmax) were determined in the selected leaves by measuring the response of photosynthesis (A; µmol m –2 s –1) to intercellular CO2 partial pressure (Ci; Pa). A portable photosynthesis system (LI-6400, Li-Cor, Lincoln, NE) equipped with a red/blue LED light source (6400-02B) was used that allowed control of PAR, temperature, humidity and CO2 concentration in the leaf chamber. The A/Ci response curves were measured in saturating light (1000 µmol m –2 s –1) by recording A at 11 values of CO2 partial pressure in the leaf chamber (35, 150, 130, 110, 100, 75, 50, 35, 25, 20, 15 and 10 Pa). The leaf was equilibrated for at least 5 min after each step change. Leaf temperature was regulated within each measurement campaign; however, a large increase in ambient temperature between April and May meant it was not possible to use a standardized leaf temperature between campaigns. Mean leaf temperature (± standard deviation) in the chamber during the April and May campaigns was 22.6 ± 0.70 and 28.8 ± 0.67 °C, respectively, whereas mean leaf to air saturation deficit in the chamber was 0.93 ± 0.18 and 1.08 ± 0.10 kPa. Data from each A/Ci curve were fitted to the formulation of the photosynthesis model given in Harley et al. (1992) based on nonlinear least-squares regression. Values for Vcmax and dark respiration, Rd, were initially determined for data where Ci < 25 Pa. Parameter Jmax was then fitted given the values for Vcmax and Rd using data where Ci exceeded the transition point between carboxylation and electron transport limited photosynthesis. Values for the kinetic constants of Rubisco (K c and K o, Michaelis constants for carboxylation and oxygenation respectively, and τ, the CO2/O2 specificity) at the measured leaf temperature were calculated using the temperature-dependence equations and parameters from Bernacchi et al. (2001). The temperature dependencies of Vcmax and Jmax were determined by measuring a series of A/Ci response curves at five leaf temperatures ranging between 11 and 37 °C. The measurements were made at Clermont-Ferrand, France (45.8° N, 3.2° E) during July on two 4-year-old trees of the “Redhaven”

931

variety growing in 0.11-m3 containers. The measurements were made in a controlled-climate room so that the entire plant was exposed to the desired air temperature. To avoid temperature acclimation, the trees were alternated daily between the climate room and outdoors. The protocol for measuring the response curves and the subsequent determination of Vcmax and Jmax were the same as that described for the field measurements, except that measurements of Rd were made in darkness before illumination of the climate room in the morning. Equations describing temperature dependence from Harley et al. (1992) were fitted to values of Vcmax and Jmax at different temperatures to yield values for the temperature-dependence parameters: Vcmax , Jmax =

exp( c − ∆Ha /(RT k )) , 1 + exp(( ∆STk − ∆H d ) /(RT k ))

Rd = exp( c − ∆H a /( RT k )) ,

(1)

(2)

where c is a scaling constant, ∆Ha and ∆Hd are the activation and deactivation energies, respectively, R is the universal gas constant, Tk is leaf temperature (K), and ∆S is an entropy term. Data from the April and May campaigns were normalized to a common reference temperature (25 °C) based on the measured temperature-dependence parameters. Following gas exchange measurements, leaves were sampled and immediately returned to the laboratory for leaf area measurement (Li-Cor LI-3000 leaf area meter). Leaf samples were dried for 2 days at 70 °C before being weighed to determine mass, then ground and a subsample analyzed for total nitrogen concentration with an elemental analyzer (Carlo Erba, Milan, Italy). Partitioning of leaf nitrogen between carboxylation (Pc; mainly in the enzyme Rubisco) and bioenergetics associated with electron transport (Pb) was calculated following the method of Niinemets and Tenhunnen (1997) using the values of Vcmax25 (Vcmax at the measured temperature normalized to 25 °C) and Jmax25 (Jmax at the measured temperature normalized to 25 °C) estimated from the A/Ci response curves and the measured Na values as: Pc = Vcmax25 /(6.25Vcr N a ),

(3)

Pb = Jmax25 /(8.06 Jmc N a ),

(4)

where Vcr is specific activity of Rubisco (µmol CO2 (g Rubisco)–1 s –1) and Jmc is potential rate of electron transport per unit of cytochrome f (cyt f ) (mol electrons (mol cyt f) –1 s –1). Both Vcr and Jmc are functions of temperature, and were computed at 25 °C with Equation 1 given the relevant parameter values for Vcmax and Jmax derived from the temperature-response measurements. The factor 6.25 (g Rubisco (g N in Rubisco) –1) converts N content to protein content, and the factor 8.06 (µmol cyt f (g N in bioenergetics)–1), which converts N content to cyt f content, assumes a constant 1:1:1.2 molar ratio for cyt f:ferredoxin NADP reductase:coupling factor.

TREE PHYSIOLOGY ONLINE at http://heronpublishing.com

932

WALCROFT, LE ROUX, DIAZ-ESPEJO, DONES AND SINOQUET

Results Crown architecture, radiation environment and leaf characteristics Over a period of 28 days, total leaf area of the tree in Avignon increased from 38.8 to 67.3 m 2, an average increase of over 1 m2 leaf area per day (Figure 1, Table 1). Leaf area index of the orchard increased from 1.55 in April to 2.69 in May. Leaves on spur shoots (i.e., those defined as less than 5 cm in length) contributed only 1.2 and 3.5% of the total leaf area in April and May, respectively. In April, the tree crown occupied 503 3-D cells for a total crown volume of 7.86 m3, whereas in May the number of occupied cells increased to 831, representing a crown volume of 12.98 m3. Because the proportional increases in leaf area and crown volume between April and May were similar, mean leaf area density (LAD) for all 3-D cells increased only slightly from 4.94 m 2 m –3 in April to 5.19 m 2 m –3 in May. Weighted according to leaf area, mean LAD was 9.3 m 2 m –3 in April and 10.2 m2 m –3 in May, and the data were negatively skewed (Figure 2a). Between April and May, the proportions of total leaf area with a local LAD of greater than 18 m 3 m –2 and less than 6 m 3 m –2 increased, whereas that between 6 and 18 m 2 m –3 decreased. During April, daily incident PAR was around 40 mol m –2 day –1, of which 33% was absorbed by the tree (Table 1). In May, daily incident PAR increased to around 49 mol m –2 day –1, and the tree absorbed 43%. The increased absorbance mainly reflected the greater number of 3-D cells containing foliage, meaning a greater area of ground was shaded. Mean leaf irradiance was lower during May than in April, but the variance increased (Table 2). The distribution of PAR a among 3-D cells containing foliage was skewed toward low PAR a values (Figure 2b). In April, half of the foliage absorbed 19% or less of incident irradiance, whereas in May half of the foliage absorbed 14% or less of incident irradiance. Between April and May there was an increase in the proportion of foliage that absorbed less than 15% of incident irradiance, with a concomitant decrease in the proportion of foliage that absorbed greater than 15% of incident irradiance (Figure 2, inset). The increase in intra-crown PAR a heterogeneity over time was paralled by an increase in the spatial variability of leaf characteristics within the crown. Mean leaf mass per unit area (Ma) decreased slightly though significantly (P = 0.014) be-

tween April and May, but the range increased by 60% and there was more than a threefold increase in sample variance (Table 2). Leaf nitrogen concentration per unit leaf mass (Nm) also declined significantly between April and May (P = 0.001); however, the range and sample variance were similar. Because leaf nitrogen concentration per unit leaf area (Na) is the product of Ma and Nm, the significant decreases in both Ma and Nm and the increase in variability of Ma over time are reflected by a significant decrease in mean Na (P < 0.001), as well as a 50% increase in both the range and sample variance. In April, variability in Ma, Nm and Na was low, and each leaf characteristic was weakly related to PAR a (Figure 3). In May, crown growth resulted in more leaves developing in regions of low PAR a (< 8 mol m –2 day –1), and these leaves had lower Ma and Na and slightly lower Nm than their respective values in April. There were no significant relationships between leaf characteristics and PAR a in April, but in May, relationships of Ma and Na against PAR a were highly significant. Relationships between all leaf characteristics and PAR a were more significant when data from April and May were combined, and revealed a nonlinear relationship between PAR a and Ma (Figure 3a, P = 0.0002). Below a PAR a of about 8 mol m –2 day –1 there was a strong positive relationship between PAR a and Ma, but above 8 mol m –2 day –1 Ma became less sensitive to PAR a. In contrast, there was a weak, though significant, linear relationship between Nm and PAR a (Figure 3b, P = 0.013). Leaf nitrogen concentration per unit leaf area (Na) was nonlinearly related to PAR a (Figure 3c, P < 0.0001), and this relationship was principally driven by Ma as opposed to Nm. Effects of leaf temperature and nitrogen content on photosynthetic capacity Both Vcmax and Jmax were strongly regulated by leaf temperature (Figures 4a and 4b). An increase in leaf temperature from 20 to 32 °C caused Vcmax to increase about fourfold, from 33 to 136 µmol m –2 s –1. Over the same temperature range, Jmax increased twofold, from 80 to 161 µmol m –2 s –1. The optimum leaf temperature for Vcmax appeared higher than that for Jmax. The different temperature sensitivities of Jmax and Vcmax are more evident when the data are normalized to a common reference temperature (25 °C, Figure 4a inset), and result in a decline in the ratio of Jmax to Vcmax with increasing temperature (Figure 5). Parameter R d increased with leaf temperature (Fig-

Figure 1. Ray-traced images of tree foliage in April (left) and May (right), illustrating the increases in leaf area and crown volume between dates.

TREE PHYSIOLOGY VOLUME 22, 2002

CROWN DEVELOPMENT AND PHOTOSYNTHETIC CAPACITY IN PEACH Table 1. Tree crown characteristics, and incident and absorbed photosynthetically active radiation (PAR) for the two sampling dates in Avignon. Leaf area index (LAI) and absorbed PAR per unit ground area were calculated on a whole-orchard basis based on the planting density (5 × 5 m spacing). Parameter

April

May

Total leaf area (m2) Shoots Spurs Leaf area index Crown volume (m3) Mean leaf area density (m 2 m –3) Incident PAR (1-week mean) (mol m –2 day –1) Absorbed PAR per unit ground area (mol m –2 day –1)

38.3 0.49 1.55 7.86 4.94 40.4 13.3

65.0 2.34 2.69 12.98 5.19 49.2 21.1

933

ure 5), and field data were consistent with those measured in a controlled environment. During the April measurement campaign, variation in Na of the leaves used in gas exchange measurements was low, with all leaves containing between 2.12 and 2.57 g N m –2. In these leaves, Vcmax25 varied between 66.5 and 108.8 µmol m –2 s –1, whereas Jmax25 varied between 149.9 and 216.9 µmol m –2 s –1. There were weak (P > 0.1) linear relationships between both Vcmax and Jmax and Na, with Na explaining about 12 and 34% of the variation in each parameter, respectively (Figure 6). The correlation was stronger with Ma, however, which explained 40 and 60% of the variation in Vcmax25 and Jmax25, respectively (data not shown). In May, Na varied from 1.26 to 2.61 g N m –2, reflecting the large increase in leaves with low Na. In contrast, the range in values of the photosynthetic parameters remained the same between April and May. The linear relationships between Vcmax25 and Jmax25 and leaf Na were significant, explaining 73 and 68% of the variation in parameter values, respectively. The correlations with Ma, however, were generally weaker, explaining 54 and 51% of the variation in Vcmax25 and Jmax25, respectively (data not shown). Photosynthetic capacity appeared to decline between April and May, with a more pronounced decline in Jmax25 than in Vcmax25. For a leaf with an Na of 2.25 g N m –2, Jmax25 was around 183 µmol m –2 s –1 in April but declined to around 120 µmol m –2 s –1 in May. Parameter Vcmax25 declined from 85 to 68 µmol m –2 s –1 over the same period. This resulted in a significant reduction in the mean Jmax25/Vcmax25 ratio from 2.0 to 1.76 (P < 0.05). Partitioning of leaf nitrogen to carboxylation processes was greater in April than in May (P < 0.01). Variability in Pc at each sampling date was low, and was unrelated to Na (Figure 7a). A similar result was observed with the bioenergetics partitioning index (Figure 7b). Parameter Pb was greater in April than in May (P < 0.001), variability in the parameter was low, and there was no relationship with Na.

Discussion

Figure 2. (a) Frequency distribution of leaf area according to leaf area density (LAD) within individual 3-D cells during April and May 1999. (b) Distribution of leaf area according to PAR a classes for leaves in the peach tree crown during April and May 1999. Values of PAR a were calculated as the mean of 4 days (April) and 7 days (May) preceding leaf sampling. The inset shows the change in frequency of LAD and PAR a in each class between the two sampling dates.

Growth of the tree crown over time resulted in the development of shade-adapted foliage in areas where PAR a was low (Figure 2). This foliage was characterized principally by low Ma (Figure 3a), but there was little effect of the changing light environment on Nm (Figure 3b). In both the April and May campaigns, the relationship between Nm and PAR a was not significant, although the relationship was significant when the two data sets were combined. There was, however, a slight though significant decline in mean Nm between the two measurement dates. The reduction was apparent in foliage from all PAR a classes, indicating that it was not a response to variation in leaf irradiance. Rosati et al. (2000) observed a uniform increase in Nm across leaf irradiance classes in response to fertilization, again indicating that light environment plays little part in determining the spatial distribution of Nm. The slight reduction in Nm in this study may have been associated with a growth dilution effect (Syvertsen and Graham 1999) as wholetree leaf area nearly doubled over the 4-week interval. The

TREE PHYSIOLOGY ONLINE at http://heronpublishing.com

934

WALCROFT, LE ROUX, DIAZ-ESPEJO, DONES AND SINOQUET

Table 2. Mean, standard deviation (SD), maximum (Max) and minimum (Min) of absorbed leaf irradiance (PAR a ), leaf mass per unit area (Ma ), leaf nitrogen concentration per unit leaf mass (Nm), and leaf nitrogen concentration per unit leaf area (Na ) for the two sampling dates in Avignon. Means within rows followed by the same letter are not significantly different (P < 0.05). Parameter

April Mean

PAR a (mol m Ma (g m –2) Nm (mg g–1) Na (g m–2)

–2

–1

day )

a

10.3 56.9a 41.1a 2.34a

May SD

Max

4.66 5.07 2.62 0.273

23.6 66.7 47.0 2.84

growth of new foliage may have exceeded the capacity of the root system to take up nitrogen from the soil, because soil nutrient content in the orchard was maintained in adequate sup-

Figure 3. Relationships between (a) leaf mass per unit area (Ma ), (b) leaf nitrogen concentration per unit leaf mass (Nm), and (c) leaf nitrogen concentration per unit leaf area (Na ) and mean leaf irradiance during April (䊉) and May (䊊) 1999. The regressions lines are fitted to combined data from both dates (equations: Ma = 36.3 + 9.60 ln(PAR a ) (R 2 = 0.33, P = 0.0002), Nm = 38.1 + 0.321 PAR a (r 2= 0.16, P = 0.013) Na = 1.26 + 0.512 ln(PAR a ) (R 2 = 0.38, P < 0.0001)).

Min

Mean

2.74 46.3 35.7 1.76

b

9.43 51.7b 38.9b 2.01b

SD

Max

Min

5.76 9.49 2.74 0.414

26.4 68.9 44.2 2.83

1.73 36.3 33.7 1.25

ply by fertilization, and irrigation provided sufficient soil water to ensure transpiration was not limited. The response of Nm to variation in light environment is diverse, and may increase (Kull and Niinemets 1993, Warren and Adams 2001), decrease (Ellsworth and Reich 1992) or remain constant (Ellsworth and Reich 1993, Hollinger 1996) with increasing light exposure. Previous studies on peach have shown that Nm is relatively insensitive to gradients in ambient light (DeJong 1986, Rosati et al. 1999, 2000, Le Roux et al. 2001). Rather, acclimation to changes in radiation environment in this species is manifested predominately by changes to

Figure 4. Temperature responses of (a) maximal rate of RuBP carboxylation (Vcmax) and (b) maximal electron transport capacity (Jmax) measured on container-grown plants in a controlled temperature room. Also shown are parameter values for the fitted curves obtained with Equation 1. Inset: The temperature responses of Vcmax (dashed line) and Jmax (solid line), normalized at 25 °C.

TREE PHYSIOLOGY VOLUME 22, 2002

CROWN DEVELOPMENT AND PHOTOSYNTHETIC CAPACITY IN PEACH

935

Figure 5. Temperature responses of (a) the ratio Jmax/Vcmax, and (b) the rate of respiration in the dark (Rd). Data are from measurements on container-grown plants in a controlled temperature growth chamber (䊉), and a field-grown tree (䊊). The regression line in (b) is fitted only to data from the growth chamber, and parameter values relate to Equation 2.

Ma (Rosati et al. 1999, 2000, Le Roux et al. 2001), and to a lesser extent by changes in nitrogen partitioning between light harvesting, carboxylation and electron transport pools (Le Roux et al. 2001). This is consistent with the results of our study, where the range of Ma values increased by 50% between April and May and were strongly related to PAR a, whereas the range of Nm values decreased between April and May and were weakly related to PAR a (Figure 3). Marini and Sowers (1990) observed that Ma in peach foliage declined in response to shading, so that after 18 days there was a positive, linear relationship between Ma and absorbed irradiance. The effect was reversible with equal rapidity, and was driven by changes in leaf mass rather than leaf area, indicating the responses may have been partly a result of changing soluble carbohydrate or starch concentrations in the leaves. In contrast, Frak et al. (2001) showed that, when a step change in irradiance was imposed on expanded walnut leaves, Ma remained largely unchanged and acclimation occurred through changes in Nm and nitrogen partitioning between photosynthetic functions. The relationship between Ma and PAR a was not significant in April, but was highly significant in May, and was also significant for the combined data sets (Figure 3). This was primarily because of the development of leaves with low Ma at

Figure 6. Values of (a) Vcmax25, (b) Jmax25 and (c) the ratio Jmax25/ Vcmax25 as functions of Na. Data are from measurements made during April (䊉) and May (䊊) in the orchard at Avignon. Linear regressions are shown where significant (P < 0.05).

mean daily PAR a values of less than 8 mol m –2 day –1. Above this threshold value, Ma was relatively insensitive to PAR a. Increases in the slope and correlation significance of relationships between both Ma and Na and an index of leaf irradiance over time was reported by DeJong and Doyle (1985) for a peach tree. This was attributed to the increase in self-shading of foliage as the tree crown developed. Marini and Marini (1983) found that leaves of low Ma developed only in areas of the tree receiving less than 40% of available PAR. The existence of a threshold PAR value, above which Ma is relatively insensitive to increased PAR, supports the conclusion of Le Roux et al. (2001) that the relationship between Ma and PARa is nonlinear in peach. Our values of Vcmax25 appear higher than those recently reported for peach, whereas the Jmax25 values are similar. Le Roux et al. (2001) and Rosati et al. (1999) presented values for Vcmax25 between 17 and 78 µmol m –2 s –1 and for Jmax25 between 50 and 265 µmol m –2 s –1 (data from Le Roux et al. (2001) and

TREE PHYSIOLOGY ONLINE at http://heronpublishing.com

936

WALCROFT, LE ROUX, DIAZ-ESPEJO, DONES AND SINOQUET

Figure 7. Proportions of leaf nitrogen partitioned to (a) carboxylation by the Rubisco enzyme (Pc) and to (b) bioenergetics by electron transport (Pb), both plotted as functions of Na. Closed and open circles represent measurements in April and May, respectively.

Rosati et al. (1999) were originally measured at 30 °C and 27 °C, respectively, and have been recalculated at 25 °C for comparative purposes). In our study, Vcmax25 varied between 37 and 108 µmol m –2 s –1 and Jmax25 varied between 70 and 217 µmol m –2 s –1. The apparently greater Vcmax in our study may be an artefact caused by using the parameters of Bernacchi et al. (2001) for Kc, Ko and τ when deriving Vcmax from A/Ci responses. Before the paper of Bernacchi et al. (2001), the parameters of Jordan and Ogren (1984) were widely used. Calculations show that, for the same A/Ci data set, the parameters of Bernacchi et al. (2001) give a value of Vcmax25 about 1.5 times higher at 25 °C than the value calculated from the parameters of Jordan and Ogren (1984). This ratio is sensitive to temperature and Ci, increasing nonlinearly with temperature from 1.3 at 5 °C to 1.5 at 40 °C (at 20 Pa Ci), and declining with Ci from 1.5 at 10 Pa to 1.2 at 100 Pa (at 25 °C). Determination of Jmax is affected to a lesser extent than Vcmax, because it is independent of Kc and Ko. When the A/Ci response curves were reanalyzed using the parameters of Jordan and Ogren (1984), the range in Vcmax25 was 25–72 µmol m –2 s –1, which is similar to two other recent studies, whereas the range in Jmax25 was 70–220 µmol m –2 s –1. This highlights the importance of analyzing data sets by a common methodology when comparing data from the literature (Medlyn et al. 2002a). Relationships between leaf photosynthetic capacity and Na were not constant within the growing season. Photosynthetic capacity appeared to decline between April and May so that, for a given unit of leaf nitrogen, both Vcmax25 and Jmax25 were

greater in April than in May (Figure 6), and this was reflected in a decrease in the partitioning coefficients Pc and Pb (Figure 7). This result was independent of whether Vcmax25 and Jmax25 were determined using the Bernacchi et al. (2001) or Jordan and Ogren (1984) parameters. Although we cannot rule out that this finding may be an artefact resulting from measuring different trees in April and May, the fact that the trees were clones and located less than 10 m apart reduces the chances that genetic or environmental factors influenced the results. Considerable spatial and temporal variability in leaf photosynthetic capacity has recently been documented in a range of deciduous forest tree species (Wilson et al. 2000). Spatial variability was primarily related to gradients in light environment through the canopy, and mediated by changes in Ma rather than Nm. Temporal variability was found to be related to soil water availability and leaf age. The leaf age effect was characterized by temporal variation in the relationship between Vcmax and Na. Temporal reductions in photosynthetic capacity have also been reported in hybrid walnut (Juglans nigra × regia), and were accompanied by a reduction in the allocation of leaf N to carboxylation processes (Frak et al. 2001). Medlyn et al. (2002b) showed that photosynthetic capacity of maritime pine (Pinus pinaster Ait.) declined as temperature increased in the summer, consistent with the present study. The use of process-based models to simulate processes of carbon assimilation over time periods greater than 1 month may require consideration of temporal changes in leaf photosynthetic capacity to accurately predict carbon uptake rates (Wilson et al. 2001, Medlyn et al. 2002b). In fruiting trees selected for high crop loads such as peach and apple, the changing balance between carbon sources and sinks through the growing season may also influence leaflevel photosynthetic capacity. Numerous studies have shown a positive relationship between leaf photosynthetic capacity and fruit crop load (DeJong 1986, Ben Mimoun et al. 1996). On this basis, one might expect an increase in leaf photosynthetic capacity with time as carbohydrate demand increases with fruit growth. However, this was not observed in the present study. Rather, the observed decline in photosynthetic capacity between April and May might indicate that carbohydrate supply increased more than demand, causing a feedbackinhibition of photosynthesis (Foyer 1988, Flore and Lakso 1989). Pavel and DeJong (1993) showed periods of sink-limited fruit growth occurred during Stage II of the double-sigmoid growth curve in two peach cultivars. This stage is characterized by a lag-phase in fruit dry weight increase (Chalmers and van den Ende 1975), which reduces fruit carbohydrate demand. If photosynthetic capacity in peach shows a similar seasonal pattern to other deciduous tree species (Wilson et al. 2000), it is likely that leaf photosynthetic capacity gradually declines for a significant proportion of the fruit growth period. However, this decline in capacity may be offset by the increase in leaf area as the season progresses, so that overall photosynthetic productivity is maintained. The degree to which the increase in tree leaf area between April and May offset the

TREE PHYSIOLOGY VOLUME 22, 2002

CROWN DEVELOPMENT AND PHOTOSYNTHETIC CAPACITY IN PEACH

decline in leaf-level photosynthetic capacity will be examined by simulating whole-tree carbon assimilation and fruit carbon demand with a 3-D photosynthesis model (Sinoquet et al. 2001) linked to a model of shoot and fruit growth (Lescourret et al. 1998). Conclusion Digitizing the architecture and topology of tree crowns successively over time provides an accurate, though time-consuming, means of quantifying within-season changes in tree crown characteristics such as leaf area and crown volume. Changes in these characteristics influenced the within-crown distribution of leaf irradiance. Variability in photosynthetic capacity increased over time, resulting from acclimation to varying PAR a as the crown developed. Acclimation was driven principally by changes in Ma as opposed to the amount or partitioning of leaf nitrogen. In addition, photosynthetic capacity per unit Na appeared to decline between April and May. Such effects need to be considered when modeling processes of carbon uptake over long periods. Acknowledgments We thank Stephane Ploquin, Ella Frak and Marc Vandame (INRA, Clermont Ferrand) for assistance in tree digitising, gas exchange measurements and leaf sample analysis. Françoise Lescourret and Michel Génard (INRA, Avignon) organized the field campaigns in Avignon and provided leaf area and shoot length data. Bernard Jaussely (INRA Avignon) provided technical assistance with the data loggers. This work was supported with fellowships provided by INRA (France) and the Trimble Agricultural Research Fund (New Zealand). References Ben Mimoun, M., J.-J. Longuenesse and M. Génard. 1996. Pmax as related to leaf:fruit ratio and fruit assimilate demand in peach. J. Hort. Sci. 71:767–775. Bernacchi, C.J., E.L. Singsaas, C. Pimentel, A.R. Portis, Jr. and S.P. Long. 2001. Improved temperature response functions for models of Rubisco-limited photosynthesis. Plant Cell Environ. 24: 253–259. Canham, C.D., R.K. Kobe, E.F. Latty and R.L. Chazdon. 1999. Interspecific and intraspecific variation in tree seedling survival: effects of allocation to roots versus carbohydrate reserves. Oecologia 121:1–11. Chalmers, D.J. and B. van den Ende. 1975. A reappraisal of the growth and development of peach fruit. Aust. J. Plant Physiol. 2: 623–634. DeJong, T.M. and J.F. Doyle. 1985. Seasonal relationships between leaf nitrogen content (photosynthetic capacity) and leaf canopy light exposure in peach (Prunus persica). Plant Cell Environ. 8: 701–706. DeJong, T.M. 1986. Distribution of leaf nitrogen concentration in relation to leaf light exposure in peach tree canopies. In Fundamental, Ecological and Agricultural Aspects of Nitrogen Metabolism in Higher Plants. Eds. H. Lambers, J.J. Neeteson and I. Stulen. Martinus Nijhoff Publishers, Dordrecht, pp 319–321. Dreyer, E., X. Le Roux, P. Montpied, F.A. Daudet and F. Masson. 2001. Temperature response of leaf photosynthetic capacity in seedlings from seven temperate tree species. Tree Physiol. 21: 223–232.

937

Ellsworth, D.S. and P.B. Reich. 1992. Leaf mass per area, nitrogen content and photosynthetic carbon gain in Acer saccharum seedlings in contrasting forest light environments. Funct. Ecol. 6: 423–435. Ellsworth, D.S. and P.B. Reich. 1993. Canopy structure and vertical patterns of photosynthesis and related leaf traits in a deciduous forest. Oecologia 96:169–178. Evans, J.R. and H. Poorter. 2001. Photosynthetic acclimation of plants to growth irradiance: the relative importance of specific leaf area and nitrogen partitioning in maximising carbon gain. Plant Cell Environ. 24:755–767. Farquhar, G.D. and S. von Caemmerer. 1982. Modelling of photosynthetic response to environmental conditions. In Encyclopaedia of Plant Physiology, New Series Vol. 12B: Physiological Plant Ecology II. Eds. O.L. Lange, P.S. Nobel, C.B. Osmond and H. Zeigler. Springer-Verlag, Berlin, pp 549–587. Field, C.B. 1983. Allocating leaf nitrogen for the maximization of carbon gain: Leaf age as a control on the allocation program. Oecologia 86:341–347. Flore, J.A. and A.N. Lakso. 1989. Environmental and physiological regulation of photosynthesis in fruit crops. Hort. Rev. 11:111–157. Foyer, C.H. 1988. Feedback inhibition of photosynthesis through source–sink regulation in leaves. Plant Physiol. 26:483–492. Frak, E., X. Le Roux, P. Millard, E. Dreyer, G. Jaouen, B. SaintJoanis and R. Wendler. 2001. Changes in total leaf nitrogen and partitioning of leaf nitrogen drive photosynthetic acclimation to light in fully developed walnut leaves. Plant Cell Environ. 24: 1279–1288. Godin, C., E. Costes and H. Sinoquet. 1999. A method for describing plant architecture which integrates topology and geometry. Ann. Bot. 84:343–357. Grossman, Y.L. and T.M. DeJong. 1994. PEACH: A simulation model of reproductive and vegetative growth in peach trees. Tree Physiol. 14:329–345. Harley, P.C., R.B. Thomas, J.F. Reynolds and B.R. Strain. 1992. Modelling photosynthesis of cotton grown in elevated CO2. Plant Cell Environ. 15:271–282. Hirose, T. and M.J.A. Werger. 1987. Maximising daily canopy photosynthesis with respect to the leaf nitrogen allocation patterns in the canopy. Oecologia. 72:520–526. Hollinger, D.Y. 1996. Optimality and nitrogen allocation in a tree canopy. Tree Physiol. 16:627–632. Jordan, D.B. and W.L. Ogren. 1984. The CO2/O2 specificity of ribulose 1,5-bisphosphate carboxylase oxygenase. Planta 161: 308–313. Kull, O. and Ü. Niinemets. 1993. Variation in leaf morphometry and nitrogen concentration in Betula pendula, Corylus avellana and Lonicera xylosteum. Tree Physiol. 12:311–318. Le Roux, X., H. Sinoquet and M. Vandame. 1999a. Spatial distribution of leaf dry weight per unit area and leaf nitrogen concentration in relation to local radiation regime within an isolated tree crown. Tree Physiol. 19:181–188. Le Roux, X., S. Grand, E. Dreyer and F.A. Daudet. 1999b. Parameterization and testing of a biochemically based photosynthesis model for walnut (Juglans regia) trees and seedlings. Tree Physiol. 19: 481–492. Le Roux, X., A.S. Walcroft, F.A. Daudet, H. Sinoquet, M.M. Chaves, A. Rodrigues and L. Osorio. 2001. Photosynthetic light acclimation in peach leaves: importance of changes in mass:area ratio, nitrogen concentration, and leaf nitrogen partitioning. Tree Physiol. 21:377–386.

TREE PHYSIOLOGY ONLINE at http://heronpublishing.com

938

WALCROFT, LE ROUX, DIAZ-ESPEJO, DONES AND SINOQUET

Lescourret, F., M. Ben Mimoun and M. Génard. 1998. A simulation model of growth at the shoot-bearing fruit level. I. Description and parameterization for peach. Eur. J. Agric. 9:173–188. Leuning, R., F.M. Kelliher, D.D.G. de Pury and E.-D. Schulze. 1995. Leaf nitrogen, photosynthesis, conductance and transpiration: scaling from leaves to canopies. Plant Cell Environ. 18:1183–1200. Marini, R.P. and M.C. Marini. 1983. Seasonal changes in specific leaf weight, net photosynthesis, and chlorophyll content of peach leaves as affected by light penetration and canopy position. J. Am. Soc. Hort. Sci. 108:600–605. Marini, R.P. and D.S. Sowers. 1990. Net photosynthesis, specific leaf weight, and flowering of peach as influenced by shade. HortScience 25:331–334. Medlyn, B.E., E. Dreyer, D.S. Ellsworth, et al. 2002a. Temperature responses of parameters of a biochemically-based model of photosynthesis. II. A review of experimental data. Plant Cell Environ. In press. Medlyn, B.E., D. Loustau and S. Delzon. 2002b. Temperature responses of parameters of a biochemically-based model of photosynthesis. I. Seasonal changes in mature maritime pine (Pinus pinaster Ait.). Plant Cell Environ. In press. Niinemets, Ü. and J.D. Tenhunen. 1997. A model separating leaf structural and physiological effects on carbon gain along light gradients for the shade-tolerant species Acer saccharum. Plant Cell Environ. 20:845–866. Niinemets, Ü., O. Kull and J.D. Tenhunen. 1998. An analysis of light effects on foliar morphology, physiology, and light interceptance in temperate deciduous woody species of contrasting shade tolerance. Tree Physiol. 18:681–696. Pavel, E.W. and T.M. DeJong. 1993. Source- and sink-limited growth periods of developing fruits indicated by relative growth rate analysis. J. Am. Soc. Hort. Sci. 118:820–824.

Rosati, A., G. Esparza, T.M. DeJong and R.W. Pearcy. 1999. Influence of canopy light environment and nitrogen availability on leaf photosynthetic characteristics and photosynthetic nitrogen-use efficiency of field-grown nectarine trees. Tree Physiol. 19:173–180. Rosati, A., K.R. Day and T.M. DeJong. 2000. Distribution of leaf mass per unit area and leaf nitrogen concentration determine partitioning of leaf nitrogen within tree canopies. Tree Physiol. 20: 271–276. Sinoquet, H., P. Rivet and C. Godin. 1997. Assessment of the three-dimensional architecture of walnut trees using digitising. Silva Fenn. 31:264–273. Sinoquet, H., X. Le Roux, B. Adam, T. Ameglio and F.A. Daudet. 2001. RATP: a model for simulating the spatial distribution of radiation absorption, transpiration and photosynthesis within canopies: application to an isolated tree crown. Plant Cell Environ. 24: 395–406. Syvertsen, J.P. and J.H. Graham. 1999. Phosphorus supply and arbuscular mycorrhizas increase growth and net gas exchange responses of two Citrus spp. grown at elevated [CO2]. Plant Soil. 208:209–219. Walcroft, A.S., D. Whitehead, W.B. Silvester and F.M. Kelliher. 1997. The response of photosynthetic model parameters to temperature and nitrogen concentration in Pinus radiata D. Don. Plant Cell Environ. 20:1338–1348. Warren, C.R. and M.A. Adams. 2001. Distribution of N, Rubisco and photosynthesis in Pinus pinaster and acclimation to light. Plant Cell Environ. 24:597–609. Wilson, K.B., D.D. Baldocchi and P.J. Hanson. 2000. Spatial and seasonal variability of photosynthetic parameters and their relationship to leaf nitrogen in a deciduous forest. Tree Physiol. 20: 565–578. Wilson, K.B., D.D. Baldocchi and P.J. Hanson. 2001. Leaf age affects the seasonal pattern of photosynthetic capacity and net ecosystem exchange of carbon in a deciduous forest. Plant Cell Environ. 24: 571–583.

TREE PHYSIOLOGY VOLUME 22, 2002