Summary Understanding seasonal changes in photosynth-etic parameters and stomatal conductance is crucial for model-ing long-term carbon uptake and energy fluxes of ecosystems.Gas exchange measurements of CO2 and light response curveson blue oak leaves (Quercus douglasii H. & A.) were con-ducted weekly throughout the growing season to study the sea-sonality of photosynthetic capacity (Vcmax) and Ball-Berryslope (m) under prolonged summer drought and high tempera-ture. A leaf photosynthetic model was used to determine Vcmax.
There was a pronounced seasonal pattern in Vcmax. The max-imum value of Vcmax, 127 µmol m–2 s–1, was reached shortly af-ter leaf expansion in early summer, when air temperature wasmoderate and soil water availability was high. Thereafter,Vcmax declined as the soil water profile became depleted andthe trees experienced extreme air temperatures, exceeding40 °C. The decline in Vcmax was gradual in midsummer, how-ever, despite extremely low predawn leaf water potentials(Ψpd, ~ –4.0 MPa). Overall, temporal changes in Vcmax werewell correlated with changes in leaf nitrogen content. Duringspring leaf development, high rates of leaf dark respiration (Rd,5–6 µmol m–2 s–1) were observed. Once a leaf reached matu-rity, Rd remained low, around 0.5 µmol m–2 s–1. In contrast tothe strong seasonality of Vcmax, m and marginal water cost perunit carbon gain (∂ ∂E A) were relatively constant over the sea-son, even when leaf Ψpd dropped to –6.8 MPa. The constancyof ∂ ∂E A suggests that stomata behaved optimally under se-vere water-stress conditions. We discuss the implications ofour findings in the context of modeling carbon and water vaporexchange between ecosystems and the atmosphere.
Keywords: Ball-Berry slope, dark respiration, marginal watercost per unit carbon gain, maximum carboxylation rate, maxi-mum electron transport capacity.
Introduction
The process-based biochemical model of Farquhar et al.(1980a) has emerged as the dominant paradigm for computingphotosynthesis at the leaf (Collatz et al. 1991, Harley and
Tenhunen 1991, Baldocchi 1994, Leuning et al. 1995), canopy(Baldocchi and Harley 1995, de Pury and Farquhar 1997),landscape (Kimball et al. 2000, Williams et al. 2001) and con-tinental (Sellers et al. 1996a, 1996b, Bonan 1998, Foley et al.1998) scales in modeling studies in biogeochemistry, ecohy-drology, climate and ecosystem physiology. The model ofFarquhar et al. (1980a) quantifies leaf CO2 assimilation rate(A) by considering how it is limited by either its ribulose1,5-bisphosphate (RuBP) saturation rate at low intercellularCO2 concentration (Ci) or its RuBP regeneration rate at highCi. This mechanistic model has a wide appeal for three rea-sons. First, the model can quantify how leaf photosynthesis re-sponds to changes in light, temperature, CO2, O2 and leafnitrogen. Second, the model is easy to parameterize withcuvette-based gas exchange measurements (Harley andBaldocchi 1995, Dang et al. 1998, Wilson et al. 2000a, Medlynet al. 2001). And third, the model is applicable at multiplescales because the spatial and temporal variations of its param-eters are constrained by one another (Wullschleger 1993) andbecause its model parameters scale with functional variables,such as leaf nitrogen (Schulze et al. 1994, Ellsworth and Reich1996).
Application of the Farquhar model to contemporary biogeo-science problems requires the simultaneous assessment of Ci
and stomatal conductance (g) (Leuning 1990, Collatz et al.1991, Harley and Tenhunen 1991). In principle, Ci is deter-mined based on an electrical conductance analogy betweenphotosynthesis and g. Stomatal conductance is evaluated by anempirical function that is proportional to the product of photo-synthesis and atmospheric relative humidity (RH) and is in-versely related to CO2 concentration at the leaf surface (Ca)(Ball et al. 1987, Leuning 1990, Collatz et al. 1991).
At present, we have a good understanding of how photosyn-thesis model parameters, maximum carboxylation velocity(Vcmax), maximum rate of electron transport (Jmax) and darkrespiration (Rd), vary with genus and species, plant functionaltype and leaf nitrogen content (Wullschleger 1993). Little isknown, however, about how Vcmax, Jmax, Rd and stomatal con-ductance model parameters of tree species vary over the
Seasonal trends in photosynthetic parameters and stomatalconductance of blue oak (Quercus douglasii) under prolonged summerdrought and high temperature
LIUKANG XU1 and DENNIS D. BALDOCCHI1,2
1 Ecosystem Science Division, Department of Environmental Science, Policy and Management, 151Hilgard Hall, University of California at Berkeley,CA 94720, USA
2 Author to whom correspondence should be addressed ([email protected])
Received October 21, 2002; accepted January 24, 2003; published online August 1, 2003
course of a season as leaves expand, age, experience stress, ac-climate and senesce (Dang et al. 1998, Wilson et al. 2000a,2001, Nogués and Alegre 2002). The majority of publishedstudies on the seasonal behavior of photosynthesis report vari-ations in maximum rates of photosynthesis at light saturation(Reich et al. 1991, Sullivan et al. 1996, Porte and Loustau1998), rather than estimates of Vcmax, which require measure-ment of A/Ci curves.
In most canopy modeling studies, photosynthetic capacity isspecified according to literature values, or a few short-termmeasurements at the field site, or is deduced from its relation-ship to leaf nitrogen content (e.g., Baldocchi and Harley 1995,Aber et al. 1996, Williams et al. 2001). The relationship be-tween Vcmax and leaf nitrogen is not universal, however; it var-ies with species (Wilson et al. 2000a) and canopy position(Meir et al. 2002) as a result of partial acclimation to light,among other factors.
A majority of short-term studies determine stomatal con-ductance with Ball-Berry slope values (m) around 9 (±20%)for well-watered C3 species. As soil water deficits develop, ex-perimental evidence suggests decreasing m, especially forMediterranean Quercus (oak) spp. (Tenhunen et al. 1990,Harley and Tenhunen 1991, Sala and Tenhunen 1996). Never-theless, one school of thought holds m constant but varies Vcmax
with air temperature and soil water stress (Sellers et al. 1996b,Colello et al. 1998).
Oak savanna ecosystems growing in the Mediterranean cli-mate of California are an ideal system for studying how photo-synthesis and stomatal conductance model parametersrespond to environmental change and perturbations. Oak sa-vannas exist in regions that experience prolonged summer pe-riods without rain (Major 1988), after the soil profile has beenfilled by winter and spring rainfall. As the soils dry over theseason, the trees experience a wide diurnal range of tempera-ture (e.g., 30 °C), periods with extremely high temperatures(> 40 °C), and high vapor pressure deficits (e.g., > 7.0 kPa).We note that the prolonged summer drought experienced inCalifornia is more severe than that faced by Mediterranean andAustralian savanna ecosystems. One of the lowest reportedvalues of predawn leaf water potential in the Mediterraneansavanna is –3.0 MPa (Joffre et al. 1999) and in the Australiansavanna, –2.5 MPa (Eamus et al. 2001). In contrast, oaksgrowing in the coastal range of California have been reportedto experience predawn water potentials as low as –3.5 MPa(Griffin 1973, Callaway et al. 1991), and we found values aslow as –6.8 MPa.
The purpose of our study was to quantify photosyntheticcapacity (Vcmax, Jmax and Rd) and m of blue oak (Quercusdouglasii H. & A.) leaves and to examine the seasonal varia-tion in those parameters. The specific questions addressedwere (1) how are photosynthetic capacity and m affected byleaf age, summer drought and high temperature; (2) are sea-sonal variations in photosynthesis model parameters related tochanges in leaf nitrogen content; and (3) do stomata operateoptimally under prolonged drought and high temperature.
Materials and methods
Site description
The study was conducted during the 2001 growing season inan oak–grass savanna in the foothills of the Sierra Nevada inCalifornia, USA (38°26′ N, 120°58′ W and 177 m a.s.l.). Thedominant tree species of the savanna is blue oak with a meancanopy height of 7.1 m and a maximum leaf area index of onlyabout 0.6 as measured with a plant canopy analyzer(LAI-2000, Li-Cor, Lincoln, NE). The site comprised about194 stems ha–1, with a mean diameter at breast height (DBH)of 0.199 m and a basal area of 18 m2 ha–1 (Kiang 2002). Meanarea of individual leaves was 6.1 ± 1.7 cm2 (n = 113).
Climate at the site is Mediterranean with clear days, hightemperatures and virtually no rainfall during the summer. Incontrast, the winter is relatively cold and wet. Mean annualtemperature was 16.2 °C in 2001 and precipitation was558 mm. These values are close to climatic means, determinedover 30 years at nearby weather stations (mean air temperatureis 16.3 °C and mean precipitation is 543.7 mm).
The soil of the oak–grass savanna is an Auburn, very rockysilt loam (Lithic haploxerepts). The soil contains 48% sand,42% silt and 10% clay. Bulk density of the surface layer(0–30 cm) is around 1.5 ± 0.1 g cm–3. The soil profile is about0.75 m deep and overlies fractured rock. Conventional wisdomindicates that the roots of blue oak are unable to penetrate therock layer and tap groundwater (Griffin 1973).
Environmental conditions
Air temperature and relative humidity were measured with ashielded and aspirated sensor (HMP-35 A, Vaisala, Helsinki,Finland) at our meteorological field station. Soil volumetricwater content was measured with a frequency domain reflecto-meter probe (ML2x, Delta-T Devices, Burwell, Cambridge,U.K.) at depths of 5, 20 and 50 cm. Meteorological variableswere logged at 5-s intervals with digital data loggers (CR10Xor CR23X, Campbell Scientific, Logan, UT) and were aver-aged over 0.5-h periods.
Predawn leaf water potential
Predawn leaf water potential (Ψpd) was monitored every2 weeks with a pressure chamber (Model 3000, Soil MoistureEquipment, Santa Barbara, CA). Measurements were usuallystarted 2 h before sunrise and completed by dawn. Measure-ments were made on 10 trees and two leaves per tree. The wa-ter potential of a leaf was measured immediately after it hadbeen excised with a razor blade from the crown at a height of 4to 5 m. It typically took less than 3 min from leaf excision tocompletion of the measurement.
Gas exchange measurements
All gas exchange measurements were made with a portablesteady-state photosynthetic system (Li-Cor Li-6400). The sys-tem was calibrated at the beginning and end of the seasonagainst secondary calibration gases that were referenced tostandards prepared by NOAA’s Climate Monitoring and Diag-
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nostics Laboratory. The span for water vapor was calibratedwith a Li-Cor dew point generator (Li-610). Zeros for bothCO2 and water vapor were calibrated with 99.99% nitrogengas, obtained by passing the nitrogen through soda lime andmagnesium perchlorate. Calibration results showed that thezero shifts and span for both CO2 and water vapor were negli-gible during the study.
The experiment started on April 18, 2001, shortly afterleaves unfolded. Two sets of photosynthesis (A) measurementswere conducted: the responses of leaf photosynthesis to CO2
concentration (A/Ci) and photosynthetically active radiation(A/Qp). Before making measurements, leaves were acclimatedin the chamber for more than 30 min at ambient temperature,ambient CO2 concentration (360 µmol CO2 mol–1 air) and a Qp
of 1600 µmol m–2 s–1, a value at which photosynthesis is atleast 95% saturated. For production of A/Ci curves, the CO2
concentration in the leaf chamber was raised to 1000 µmolmol–1 while exposed to constant and saturating sunlight.Leaves were allowed to equilibrate for 8 min before loggingdata. The CO2 concentration was then lowered and the proce-dure repeated. The CO2 concentrations used to generate theA/Ci curves were 1000, 700, 500, 360, 200, 150, 100 and50 µmol mol–1. For production of A/Qp curves, Qp was in-creased to 2000 µmol m–2 s–1 while the CO2 concentration waskept constant at 360 µmol mol–1. Then Qp was sequentiallylowered to 1400, 1000, 600, 400, 200, 100 and 50 µmol m–2
s–1. During gas exchange measurements, the vapor pressuredeficit (VPD) was typically 1.0 to 3.5 kPa, depending on leaftemperature and transpiration rate. A full A/Ci or A/Qp re-sponse curve usually took about 2 h to complete. All leaf gasexchange measurements were conducted between mid-morn-ing and early afternoon. During this time, leaf temperatureswere held between 25 and 33 °C.
Leaf nitrogen content
After gas exchange measurements were made, leaves werecollected for analysis of area, mass per area (LMA) and nitro-gen content. Leaf area was determined with an optical areameter (Li-Cor Li-3100). Leaves were oven dried at 70 °C for atleast 48 h to assess dry mass. Leaf samples were ground andnitrogen content determined by mass spectrometry (20-20,PDZ Europa, Sandbach, U.K.).
Calculation of Vcmax, Jmax and Rd
The parameters Vcmax, Jmax, and Rd were estimated from A/Ci
curves by nonlinear regression. It is generally assumed that Ais limited solely by the maximum rate of carboxylation at lowCi (Farquhar et al. 1980a). Therefore, Vcmax and Rd were esti-mated from the lower region of A/Ci curves, where Ci was lessthan 150 µmol mol–1.
( )AO
C
V C
C K O KR= −
+ +−1
05
1
.
τ i
cmax i
i c od (1)
where O and Ci are the partial pressures of oxygen and CO2 inthe intercellular air space, τ is the Rubisco specific factor (de-
fined as V K V Kcmax o omax c), Kc and Ko are the Michaelis-Menten constants for CO2 and O2, respectively, and Rd repre-sents CO2 evolution from mitochondria in the light, rather thanthat from photorespiratory carbon oxidation (Farquhar et al.1980a).
At higher Ci exposures, A is limited by the regeneration ofRuBP via electron transport. Hence, Jmax can be estimatedfrom the A/Ci curve when Ci exceeds 250 µmol mol–1.
( )AO
C
JC
C OR= −
+−1
05
4
.
τ τi
i
id (2)
where J is the potential rate of electron transport and is de-pendent on photon flux and Jmax:
( )J
I
I J=
+
α
α12
max
(3)
where I is the absorbed photon flux density and α (0.24) is theefficiency of light conversion. We normalized Vcmax, Jmax andRd to 25 °C according to Equations 8 and 9 of Harley et al.(1992), and the temperature coefficients were from Bernacchiet al. (2001). A complete list of model parameters and theirunits is given in Table 1.
Stomatal conductance was evaluated by the Ball-Berry em-pirical stomatal conductance model (Ball et al. 1987):
g g mA
C= +0
RH
a
(4)
where RH is the relative humidity at the leaf surface, Ca is theCO2 concentration at the leaf surface, and g0 and m are the in-tercept and slope obtained from least squares regression. Todetermine these parameters, we used only the data when CO2
concentration was higher than ambient. This procedureavoided the poor behavior of the Ball-Berry model at sub-am-bient atmospheric CO2 concentrations when photorespirationrates increase disproportionately (Leuning 1995).
A long time step (8 min) was used to generate A/Ci and A/Qp
curves because stomata respond more slowly to changes in en-vironmental conditions than photosynthesis (Pearcy 1990).Shorter time steps are problematic because they cause unstableestimates of m. This problem became evident during prelimi-nary tests, when we found that m and the coefficient of deter-mination of the regression (r 2) were sensitive to the time step.For example, when a 3-min time step was used we found thatm = 1.6 and r 2 = 0.13. Increasing the time step to 8 min pro-duced m = 8.75, in line with literature values (Collatz et al.1991), and r 2 = 0.91.
Calculation of ∂ ∂E A
Marginal water cost per unit carbon gain (∂ ∂E A) was com-puted from ∂ ∂E g and ∂ ∂A g as described by Farquhar et al.(1980b). The partial derivative ∂ ∂E g was computed accord-ing to an Ohm’s Law model for vapor transfer:
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SEASONAL VARIATIONS IN PHOTOSYNTHETIC PARAMETERS OF BLUE OAK 867
∂∂E
g
w
g b=
+∆
1(5)
where b r H= 1 ε b and ∆w is the difference in the mole fractionof water vapor inside and outside the leaf. The variable ε repre-sents the rate of increase of latent heat content in saturated airwith respect to an increase in sensible heat content. It is a func-tion of leaf temperature, and was computed with a regressionequation obtained by Thomas et al. (1999a). The boundarylayer resistance for heat, r H
b , was computed from
1 1
112
8 3
r r
T
CHb b p
= +.
σ(6)
where rb is the boundary layer resistance for heat transfer, Cp isthe heat capacity of air at constant pressure, and σ is Stefan’sconstant. The second term on the right-hand side of Equation 6represents the resistance to heat transfer by long-wave radia-tion, assuming unit emissivity and considering transfer fromboth sides of the leaf in parallel (Cowan 1977).
The term ∂ ∂A g was obtained from the empirical relation-ship:
AK g
K K g=
+1
2 3
(7)
where A is the net CO2 assimilation rate. The constants K1, K2
and K3 were fitted by nonlinear least squares regression. Thepartial derivative ∂ ∂A g can be expressed:
∂∂A
g
K
K K g
K K g
K K g=
+−
+1
2 3
1 3
2 3
(8)
The method used to assess ∂ ∂E A was a simplified version
of a larger set of equations (Thomas et al. 1999a). Applicationof the simplified version requires that leaf boundary layer re-sistance be small and leaf temperature be near the optimum forphotosynthesis (Field et al. 1982), which were valid assump-tions in this study.
Results
Weather and soil water content
To assess seasonal variation in leaf photosynthesis and stoma-tal conductance model parameters, we need detailed informa-tion on the seasonality of key environmental drivers. Seasonalvariations in daily maximum air temperature (Tair_max), dailyminimum air temperature (Tair_min), daytime mean VPD, volu-metric soil water content (θv) and precipitation are presentedin Figure 1. Daytime mean VPD was averaged for the periodfrom sunrise to sunset. After leaves unfolded (~ Day 100),maximum air temperatures increased markedly with time,ranging from moderate (~ 10 °C) in the spring to extreme(> 40 °C) by early summer (Figure 1a). The high air tempera-tures in early summer approached values that inhibit manyphotosynthetic processes (Björkman 1981). Minimum tem-peratures in the summer were between 10 and 20 °C, so thatleaves experienced a 20 to 30 °C range in temperature over thecourse of a day.
Leaves experienced much day to day variation in VPD.Mean daytime vapor pressure deficit swung between 1 and5 kPa within a few days when air masses changed (Figure 1b).The general pattern, though, was a progressive increase inVPD corresponding with the seasonal rise in air temperature.However, there were frequent episodes when leaves experi-enced a VPD as high as 7.5 kPa in the afternoon (hourly datanot shown).
Total precipitation in 2001 was 558 mm, which was close to
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Table 1. Values and units of parameters used to compute maximum carboxylation velocity (Vcmax), maximum rate of electron transport (Jmax)and leaf dark respiration (Rd) from leaf gas-exchange data, and their temperature-dependent parameters for normalizing the photosynthetic pa-rameters to 25 °C. Temperature-dependent parameters are from Bernacchi et al. (2001), and other paramters are from Harley et al. (1992).
Parameter Description Value Unit
Kc Michaelis-Menten constant for CO2 (25 °C) 275.0 µmol mol–1
Ko Michaelis-Menten constant for O2 (25 °C) 420.0 mmol mol–1
τ Specificity factor for Rubisco 2321 –
∆Ha(Kc) Activation energy for temperature dependency 79.43 kJ mol–1
∆Ha(Ko) 36.38 kJ mol–1
∆Ha(τ) –29.0 kJ mol–1
∆Ha(Rd) 46.39 kJ mol–1
∆Ha(Vcmax) 65.33 kJ mol–1
∆Ha(Jmax) 79.5 kJ mol–1
∆Hd(Vcmax) Deactivation energy for temperature dependency 202.9 kJ mol–1
∆Hd(Jmax) 201.0 kJ mol–1
∆S(Vcmax) Entropy term for temperature dependency 0.65 kJ K–1 mol–1
∆S(Jmax) 0.65 kJ K–1 mol–1
the normal. About 98% of the precipitation fell in the wet sea-son (October–April). The last rainfall (24.1 mm) was on April21 (Day 111, Figure 1c).
There was enough winter precipitation to recharge the soilwater profile. Volumetric soil water content, averaged from 5-,20- and 50-cm depths, was near field capacity if not higher inthe wet season. Within a month after the last winter rainfall, θv
declined to a steady-state low of about 0.11 cm3 cm–3 (Fig-ure 1d). A shallow soil profile, relatively light soil texture andhigh evaporative demand contributed to the rapid depletion ofsoil water.
Leaf ecophysiological parameters
Seasonal variations in Ψpd, LMA, leaf nitrogen content perunit area (Na), g, maximum net photosynthetic rate (Amax) andCi/Ca ratio are presented in Figure 2. We defined Amax as therate of photosynthesis at ambient CO2 concentration(360 µmol mol–1) and saturating Qp (1600 µmol m–2 s–1). Dur-ing the early growing season, Ψpd was around –0.3 MPa, indi-cating high soil water availability (Figure 2a). As the growingseason progressed and the trees extracted water from the soilprofile, Ψpd diminished continually. By midsummer, Ψpd wastypically below –3.0 MPa and by the end of the summer it hadfallen to –6.8 MPa. We note that Ψpd continued declining inthe summer even after the integrated soil water content hadreached an asymptote near 0.11 cm3 cm–3.
Both LMA and Na increased rapidly during early leaf de-velopment (before Day 112). Thereafter LMA continued toincrease gradually for the rest of the season, whereas Na de-creased (Figures 2b and 2c).
Seasonal changes in g and Amax showed a similar patternduring the growing season (Figures 2d and 2f). They increasedrapidly in spring until the leaf reached maturity and then grad-ually declined until leaf senescence in September. The peakvalues of g and Amax lasted only about 2–3 weeks, a relativelyshort period compared with many other plant species (Wilson
et al. 2000a). The pronounced decline in Amax and g was pre-sumably a result of the negative impacts of water deficits andextreme temperatures (Björkman 1981, Cornic 1994). We notethat maximum Amax occurred 2 to 3 weeks after maximumLMA was reached, suggesting that physiological activity ofthe leaf continued after structural development had stopped.High rates of Rd (see following section) also support this con-clusion.
The Ci/Ca ratio (Figure 2f) declined over the season from 0.7to 0.5. Low Ci/Ca values were an artifact of drought-inducedstomatal closure and the subsequent readjustment between thesupply and demand for carbon dioxide.
Variations in Vcmax, Jmax and Rd
Strong seasonal variations in the photosynthesis model param-eters (Vcmax, Jmax and Rd) are shown in Figure 3. During leaf de-velopment, Vcmax and Jmax increased rapidly with time andreached maximum values of 127 and 345 µmol m–2 s–1, re-spectively, around Day 137 (Figures 3a and 3b). As observedfor Amax, the period of maximum photosynthetic capacitylasted less than 3 weeks. Thereafter, there was a rapid declinein Vcmax and Jmax, as the leaves experienced water deficits andextreme air temperatures. From mid- to late summer, Vcmax de-creased slowly with time, whereas Ψpd continued to decreasemarkedly (Figure 2a). Toward the end of the growing season,there was another rapid decline in Vcmax caused by leaf senes-cence as Ψpd approached the extreme low of –6.8 MPa.
Dark respiration was high during leaf development (Fig-ure 3c) and then gradually declined as leaves matured. Onceleaves were fully mature, as indicated by maximum Vcmax, Rd
remained relatively stable around 0.5 µmol m–2 s–1.
Relationship between Vcmax and leaf N
To determine whether the temporal variation in Vcmax was me-diated through changes in leaf nitrogen content, pooled datawere analyzed by simple linear regression. There was a strong
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SEASONAL VARIATIONS IN PHOTOSYNTHETIC PARAMETERS OF BLUE OAK 869
Figure 1. Seasonal variations in dailymaximum air temperature (Tair_max),minimum air temperature (Tair_min),mean daytime air vapor pressure deficit(VPD), soil volumetric water content(θv) averaged from 0 to 50 cm, anddaily precipitation. Mean daytime VPDwas for the period between sunrise andsunset. Annual precipitation was558 mm.
correlation between mass-based Vcmax_m (µmol g–1 s–1) and leafnitrogen concentration Nm (g g–1) (r 2 = 0.71, intercept –0.86,slope 72.18, n = 51, P < 0.0001) (Table 2). On the other hand,correlation on an area basis (Vcmax_a versus Na) was weak (r 2 =0.31, intercept –56.42, slope 47.38, P < 0.0001), even though
the relationship was significant. The poor correlation was mostlikely caused by a corresponding temporal change in LMA.Previous studies have shown that LMA is negatively corre-lated with leaf A (Reich and Walters 1994, Reich et al. 1997,1999, Peterson et al. 1999). To control the effect of LMA on
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Figure 2. Seasonal trends in predawnwater potential (Ψpd), leaf mass perarea (LMA), leaf nitrogen content perunit area (Na), stomatal conductance(g), ratio of intercellular to atmosphericCO2 concentration (Ci /Ca) and maxi-mum net photosynthesis (Amax). TheΨpd data represent the means and stan-dard deviations of a minimum of 18measurements. Values of g, Ci /Ca andAmax were obtained from A/Ci andA/Qp curves at ambient CO2 concentra-tion (360 µmol mol–1) and saturatedQp (1600 µmol m–2 s–1).
Figure 3. Seasonal trends of maximumcarboxylation rate (Vcmax), maximumelectron transport capacity (Jmax) anddark respiration (Rd). Data were nor-malized to 25 °C.
Vcmax, we used a multiple linear regression of the form Vcmax =b0 + b1Nleaf + b2LMA. We found that the slopes (b1) for mass-and area-based multiple regressions were the same (Table 2).This result is consistent with the work of Peterson et al. (1999),who showed that b1 was independent of the unit of expressionwhen the effect of LMA was included in the regression. Fur-thermore, multiple regression improved r 2 from 0.31 to 0.70.
Impact of Ψpd on g
To quantify the impact of soil water deficits on the physiologi-cal functioning of leaves, we plotted g against Ψpd (Figure 4).Stomatal conductance decreased with decreasing Ψpd in a non-linear fashion. These data differ from those reported by others(Hsiao 1973, Biscoe et al. 1976), which showed a thresholdvalue of Ψpd at which stomatal closure is observed.
Ball-Berry slope and ∂ ∂E A
We assessed the Ball-Berry stomatal conductance model usingA/Ci and A/Qp measurements from the whole season. Specifi-cally, we plotted g against ARH/Ca (Figure 5). The correlationbetween g and ARH/Ca was linear and significant (r 2 = 0.88,P < 0.0001). The value of m was 8.88, typical for oak (Harleyand Baldocchi 1995), and the intercept was 0.006 mol m–2 s–1.The strong correlation between g and ARH/Ca during the
growing season suggests that leaf age and severe water stressdid not alter m for blue oak. The constancy of m has significantimplication for the application of coupled photosynthesis–stomatal conductance models, which are often used as sub-models in larger-scale modeling studies, for example, SiB2(Sellers et al. 1996b) and LSM (Bonan 1998).
The finding that severe water stress and extremely high airtemperature did not alter m led us to ask: do stomata operateoptimally under such unfavorable conditions? To answer thisquestion, we examined ∂ ∂E A with the results presented inFigure 6a. We found that ∂ ∂E A was fairly constant for thewhole season, except for the data sets from April 18 and 27(Days 108 and 117, respectively). We also observed that∂ ∂E A was invariant across the range of Ψpd values (Fig-ure 6b). These data suggest that stomatal behavior of blue oakis consistent with the optimal water use theory of Cowan andFarquhar (1977) under severe drought conditions. The lowvalues of ∂ ∂E A for the first two data sets are most likely dueto the low VPD that was experienced by the leaf in the earlyseason because the method that we used to compute ∂ ∂E A issensitive to VPD (Thomas et al. 1999b).
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Table 2. Simple and multiple linear regression coefficients for maximum carboxylation velocity (Vcmax) versus leaf N content (N ) and leaf massper area (LMA) on mass and area bases (n = 51). Units: Vcmax_a = µmol m–2 s–1; Vcmax_m = µmol g–1 s–1; Na = g m–2; Nm = g g–1; and LMA = g m–2.Abbreviation: na = not applicable.
Figure 4. Relationship between predawn water potential (Ψpd) andstomatal conductance (g). Values of g represent the mean and standarddeviation of 3–6 measurements. Values were obtained from gas ex-change measurements conducted after leaves fully matured.
Figure 5. Relationship between measured stomatal conductance (g)and the product of net photosynthesis (A; µmol mol–1) and relative hu-midity (RH) divided by external CO2 concentration (Ca; µmol mol–1).Only data when Ca > 360 µmol mol–1 were used. The linear regressionequation is g = 8.88ARH/Ca + 0.006 (r2 = 0.88, P < 0.0001).
Discussion
Comparison of Vcmax in blue oak with data for the Quercusgenus and other tree species
The maximum value of Vcmax (127.3 µmol m–2 s–1; May 17(Day 137)) was 30% higher than most published values for thesame genus. Dreyer et al. (2001), for example, reported Vcmax
of 87.7 and 90.5 µmol m–2 s–1 in Quercus petraea Matt. Liebl.and Quercus robur L., respectively, for nursery-grown plantsin shade. Wilson et al. (2000a) and Harley and Baldocchi(1995) studied fully sunlit white oak (Quercus alba L.) andchestnut oak (Quercus prinus L.) trees near Oak Ridge, Ten-nessee and reported a maximum Vcmax of 78 µmol m–2 s–1.Turnbull et al. (2002) reported values of Vcmax that ranged be-tween 44 and 57 µmol m–2 s–1 for Quercus rubra L. andQ. prinus at a field site in New York State. We note that themaximum Vcmax for blue oak is outside the range (11–119 µmolm–2 s–1, mean 47 µmol m–2 s–1) of a variety of broad-leaveddeciduous tree species (Wullschleger 1993).
Significance of high Vcmax values
It is well known that tree species adapt to prolonged droughtand high irradiances and temperatures by developing smallthick leaves (Nobel 1977, Groom and Lamont 1997). A recentcompilation of data for 558 broad-leaved and 39 needle-leavedtree species at 182 geographic locations confirmed a positivecorrelation between solar radiation and LMA and a negativecorrelation between mean precipitation in the driest 3 monthsand LMA (Niinemets 2001). Therefore, we conclude that thehigh LMA (> 160 g m–2) and area-based nitrogen concentra-tion (3.5 g m–2, Figure 2c) of blue oak leaves are adaptations tohigh irradiances and prolonged summer drought on leaf mor-phology. We also conclude that small thick leaves rich in nitro-gen have high photosynthetic capacity. This conclusion isbased on the observation that maximum leaf photosynthesisrates correlate positively with leaf nitrogen (Field 1983).
The reason why Vcmax is higher in blue oak than in other treespecies can be deduced from leaf nitrogen concentrations. Oursurvey of the literature indicates that published values of area-based leaf nitrogen in oak leaves rarely exceed 3.0 g m–2
(Reich et al. 1991, Reich et al. 1998, Meir et al. 2002, Turnbullet al. 2002). Because nitrogen concentrations of blue oakleaves exceed those of other oak species, they must have the
structure and capacity (e.g., ample Rubisco) to achieve highVcmax values (see Table 2).
Seasonality of Vcmax and its association with severe soil waterdeficits and high temperature
Dynamic seasonal changes in environment and phenology re-sulted in a strong seasonality of photosynthetic parameters.The seasonal pattern of Vcmax was divided into five phases: (1)leaf development; (2) spring maximum; (3) early summer fastdecline; (4) gradual summer decline; and (5) leaf senescence.
During the leaf development phase, Vcmax increased steadilyas the leaf matured; however, Vcmax did not reach the springmaximum until about 2 weeks after LMA had reached steadystate. This suggests that leaf development had not ended whenLMA reached steady state. The high Rd after leaf expansion(Figure 3c) also indicates that the leaf had not reached matu-rity. Similar results have been reported for evergreen broad-leaved tree species in Japan (Miyazawa et al. 1998). Thus, itmay not always be true that maximum photosynthetic rate on aleaf area basis occurs around the end of leaf expansion.
The fast decline phase of Vcmax started around Day 144 (Fig-ure 3a), coinciding with the onset of summer drought, as indi-cated by soil water content (Figure 1d) and predawn leaf waterpotential (Figure 2a). Many mechanisms underlying drought-induced reduction in photosynthetic capacity have been identi-fied, including increased mesophyll resistance (Pearcy 1983);reduced Rubisco activity (Medrano et al. 1997, Parry et al.2002); and reduced electron transport capacity (Epron andDreyer 1992, Sanchez-Rodriguez et al. 1997). Unfortunately,however, the dominant mechanism responsible for the fastdecline in Vcmax cannot be determined without other physiolog-ical measurements. Future measurements of chlorophyll fluo-rescence (Valentini et al. 1995) and analysis of stomatal versusnonstomatal limitations (Wilson et al. 2000b) will help.
Besides drought, high temperature probably contributed tothe fast early summer decline in Vcmax. As illustrated in Fig-ure 1a, leaves experienced many days when Tair_max exceeded40 °C. With partial stomatal closure and low transpirationrates, leaves probably experienced temperatures greater thanair temperature. Physiological studies show that high tempera-tures decrease photosynthesis by reducing PSII activity(Björkman and Powles 1984, Weiss and Berry 1988, Epronand Dreyer 1992). Damage to PSII as a result of high tempera-
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Figure 6. Marginal water cost per unitcarbon gain as a function of day ofyear (a) and predawn water potential(b).
ture can be more severe when plants are drought stressed(Hamerlynck et al. 2000), as occurred in this study. Because ofthe temporal correspondence between leaf nitrogen concentra-tion and Vcmax, we conclude that these environmental stressesaffected structural and biochemical properties of the leaf asquantified by leaf nitrogen, and produced the decline in Vcmax.
The rate of decline in Vcmax decreased during the middle ofthe summer when water-loss due to tree transpiration was re-duced by stomatal closure. Trees may have been able to tapgroundwater, for fine roots can penetrate through the crevicesof bedrock. The mild air temperature and low VPD experi-enced during the period may also have contributed to the re-duced rate of decline in Vcmax.
A reduction in leaf nitrogen concentration was not the onlyfactor that limited photosynthetic capacity. We found that ni-trogen-use efficiency (NUE; defined as mol CO2 assimilatedper g leaf nitrogen) also decreased over the study period(Figure 7). This is consistent with other reports on NUE indrought-afflicted deciduous tree species (Reich et al. 1989,Abrams and Mostoller 1995), but is not a universal finding.Wilson et al. (2000a) reported that drought-related reductionin Vcmax did not correlate with changes in leaf nitrogen content.They explained their result in terms of a seasonally dependentchange in the fractional allocation of leaf nitrogen to Rubisco.
High NUE early in the growing season came at the cost ofmaintaining high water-use efficiency (WUE; CO2 assimilatedper mol of H2O transpired), as illustrated in Figure 7. As wateravailability decreased later in the season, WUE improvedwhile NUE decreased. Reich et al. (1989) demonstrated a sim-ilar negative correlation for Ulmus americana L. under long-term water stress. This type of relationship also exists for sev-eral desert evergreen species (Field 1983, Lajtha and Whitford1989). The inverse relationship between NUE and WUE sug-gests that blue oak trees maximize WUE or NUE dependingon which resource is most limited (Reich et al. 1989).
Constancy of m and ∂ ∂E A
The Ball-Berry stomatal model (Equation 4) developed by
Ball et al. (1987) has become popular because it couples sto-matal conductance with important physiological andenvironmental variables, i.e., photosynthetic rate, relative hu-midity and CO2 concentration. Furthermore, many short-termexperimental data have shown that the model accounts formost of the variation in stomatal response between differentspecies exposed to different temperature, light, humidity(Collatz et al. 1991, 1992) and CO2 regimes (Medlyn et al.2001). Detailed studies on how water stress and leaf age affectm are lacking, however.
Harley and Tenhunen (1991) showed that m decreased asleaves aged. Because of insufficient data, they did not estimatem by linear regression of ARH/Ca and g. Instead, they inter-preted m values so that an appropriate Ci value of 200 to240 µmol mol–1 was produced. This method of obtaining mvalues is prone to errors, because Ci can change, especially un-der stress conditions (Sage 1994).
The effect of decreasing soil water content on m is in dis-pute. Several European teams working with Mediterraneantrees (e.g., Harley and Tenhunen 1991, Sala and Tenhunen1996) assert that m decreases as the soil dries. On the otherhand, scientists from the Carnegie Institute of Washington,where the Ball-Berry model was developed, assert that m re-mains constant and Vcmax decreases as the soil dries (Sellers etal. 1996b, Colello et al. 1998).
We found that the linear relationship between g and ARH/Ca
was unaffected by water stress or leaf age, indicating that mwas constant (Figure 5). This observation suggests that theresponse of stomata to water stress parallels that of photo-synthesis, reinforcing the link between stomatal conductanceand photosynthetic capacity observed under normal, nonstressconditions (Wong et al. 1979).
We also found that neither water stress nor leaf age signifi-cantly affected ∂ ∂E A, which is consistent with the optimiza-tion theory of stomatal behavior (Cowan 1977, Cowan andFarquhar 1977) and with numerous studies. Most studies,however, have focused on changes in leaf-to-air vapor pressuredifference (Farquhar et al. 1980b, Hall and Schulze 1980,Field et al. 1982). Few studies have focused on other environ-mental factors like leaf temperature (Thomas et al. 1999b), ra-diation or soil water content (Hall and Schulze 1980, Grieu etal. 1988, Thomas et al. 1999b). Thomas et al. (1999b), work-ing with potted plants, observed a decline in ∂ ∂E A as pre-dawn water potential dropped, suggesting an increase in theefficiency of stomatal behavior. So far, there are no field datashowing how ∂ ∂E A responds to changes in leaf age or soilwater content.
The simplified method that we used to calculate ∂ ∂E A wasbased on several assumptions (Field et al. 1982). The more rig-orous method to evaluate ∂ ∂E A proposed by Cowan andFarquhar (1977) requires data on maximum, minimum and op-timum leaf temperature for photosynthesis over the growingseason—data that were unavailable to us.
Many studies have shown that optimal temperatures forphotosynthesis and stomatal conductance vary with seasonaland inter-annual temperature changes (Mooney et al. 1978,
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SEASONAL VARIATIONS IN PHOTOSYNTHETIC PARAMETERS OF BLUE OAK 873
Figure 7. Seasonal trends in nitrogen-use efficiency (NUE; �) andwater-use efficiency (WUE; �). The NUE data were obtained frommaximum net photosynthetic rate (Amax) and leaf N content, andWUE was the ratio of Amax to transpiration from the gas exchangemeasurements.
Dang et al. 1998, Medlyn et al. 2002a, Ogle and Reynolds2002). The constancy of ∂ ∂E A indicates that stomata behaveoptimally, i.e., they maximize the ratio of carbon gain to waterloss over the season.
Implications for biophysical models
Biochemically based photosynthesis models (Farquhar et al.1980a) are now widely used (Harley and Tenhunen 1991,Baldocchi and Harley 1995, de Pury and Farquhar 1997). Themain objective of these modeling exercises is to understandhow photosynthesis responds to environmental perturbations,including elevated atmosphere CO2 concentration, high tem-perature and drought. The key parameters in the leaf-levelphotosynthesis model are Vcmax, Jmax and Rd. Several studieshave investigated the temperature response of these parame-ters (Dreyer et al. 2001, Medlyn et al. 2002a) in order to quan-tify the relationship between them and leaf nitrogen contentfor different tree species (Harley et al. 1992, Niinemets andTenhunen 1997, Le Roux et al. 1999, Meir et al. 2002). Only afew studies have focused on seasonal variations in Vcmax, Jmax
and Rd and their relationship with leaf nitrogen content (Wil-son et al. 2000a, Medlyn et al. 2002a, Nogués and Alegre2002). We found that more than 70% of temporal variations inVcmax could be explained by changes in leaf nitrogen content(Table 2). This indicates that it is possible to predict leaf photo-synthetic parameters based on leaf nitrogen content, which isrelatively easy to obtain.
In many previous modeling exercises, Rd was assumed toscale linearly with Vcmax and LMA (Field 1983, Collatz et al.1991, 1992, Niinemets and Tenhunen 1997, Reich et al. 1998,Wohlfahrt et al. 1998). We did not observe a linear relationshipbetween Rd and Vcmax or Rd and LMA. The rate of leaf dark res-piration was high during leaf development (Figure 3c), butonce the leaf matured, Rd was relatively low. Similar results in-clude those of Wilson et al. (2000a), who found that Vcmax wasfairly insensitive to Rd, and Miyazawa et al. (1998), who ob-served high Rd before full leaf maturation in six evergreen treespecies. Thus, the method of interpolating Rd from Vcmax andLMA needs to be reconsidered.
Another important parameter in the coupled photosynthe-sis–Ball-Berry stomatal conductance model is m. Althoughthe Ball-Berry model is empirical, it is easy to parameterizecompared with other more sophisticated models (e.g., Jarvis1976). We found that neither leaf age nor water stress signifi-cantly affected m (Figure 5). Other studies have shown that, formany species, m does not change in response to elevated CO2
concentration (Harley et al. 1992, Medlyn et al. 2001). Thus asingle value of m may be applicable under most conditions ex-pected in the near future, including elevated atmospheric CO2
concentration, severe drought and high temperature. With aconstant value of m, Baldocchi and Meyers (1998) were ableto predict CO2 and water vapor fluxes that agreed with eddycovariance measurements for wheat, soybean, boreal coniferand temperate deciduous forest.
The parameter Vcmax was highly correlated with Amax (Fig-ure 8). This relationship could be used to obtain Vcmax in cases
where it is too time-consuming to produce A/Ci curves. Tem-poral variations in Jmax also correlated well with changes inVcmax after a curvilinear fashion. The ratio Jmax/Vcmax variedfrom around 2.5 in spring when Vcmax was at a maximum toaround 1.0 in the senescence phase, suggesting that seasonalchanges in N allocation to electron transport and Rubisco donot occur in parallel. Our values of Jmax/Vcmax were lower thanthose reported by Wilson et al. (2000a), who also showed thatthe slope was seasonally dependent, ranging from 2.11 to 3.33in oak, maple and sugar maple species. In a study of broadleafand coniferous species, Medlyn et al. (2002b) reported thatJmax/Vcmax varied considerably among species with a mean of1.67. Thus, Jmax/Vcmax may be species-specific and seasonallydependent—a thing to keep in mind when scaling Vcmax to Jmax.
The importance of accurate estimation of Vcmax to the perfor-mance of canopy photosynthetic models is known (Aber et al.1996, Dang et al. 1998, Wilson et al. 2001). The seasonality ofphotosynthetic parameters should be taken into account whenmodeling long-term CO2 and water vapor exchanges betweenterrestrial ecosystems and the atmosphere. In fact, Wilson etal. (2001) found that doing so led to improved agreement be-tween model predictions and measured canopy CO2 flux data.They found that the use of early season maximum Vcmax valuesfor the entire growing season overestimated carbon uptake byas much as 300 g C m–2 year–1—half the rate measured by theeddy covariance method. And with mean values of Vcmax, theywere unable to simulate the seasonality of carbon uptake bythe forest.
To model carbon exchange between terrestrial ecosystemsand the atmosphere, information is needed on the seasonalityof photosynthetic parameters and on how those parameterschange in the course of a day as the leaf experiences variationsin temperature and VPD. Several research groups have begunstudying the temperature dependence of photosynthetic pa-rameters (Bernacchi et al. 2001, Dreyer et al. 2001, Medlyn etal. 2002b). One study shows that temperature dependence maybe seasonal and species-specific (Medlyn et al. 2002b), imply-ing that studies of blue oak are needed to investigate the sea-
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Figure 8. Relationship between maximum net photosynthetic rate(Amax) and maximum carboxylation velocity (Vcmax). The linear re-gression equation is Vcmax = 4.42Amax + 16.86 (r2 = 0.90, P < 0.0001).Values were compiled from the whole season.
sonal temperature dependence of Vcmax and Jmax, especiallyunder drought conditions.
Estimates of Vcmax from A/Ci could be inaccurate if meso-phyll resistance changed or if patchy stomatal closure oc-curred, which it sometimes does under water stress conditions(Epron and Dreyer 1993, Mott 1995). Wilson et al. (2000a) re-viewed several of the effects that changed mesophyll resis-tance and patchy stomatal closure might have on estimates ofVcmax. They concluded: “including a drought-dependent Vcmax
parameterization may not be physiologically correct, but willaccurately estimate fluxes.”
In conclusion, large seasonal variations in soil water con-tent, air temperature and VPD resulted in strong seasonality inphotosynthetic capacity, including Vcmax, Jmax and Rd, and instrong stomatal control of transpiration in blue oak trees in thefoothills of the Sierra Nevada of California. Water stress andhigh temperature had significant affects on the seasonality ofthese physiological parameters. Most of the seasonal variationin Vcmax could be explained by changes in leaf nitrogen contentwhen the effect of LMA on Vcmax was controlled. The Ball-Berry slope remained fairly constant during the growing sea-son, indicating that photosynthetic capacity and stomatal con-ductance responded in parallel to seasonal changes in soilwater content and temperature. Therefore, the Ball-Berry rela-tionship can be applied under water stress conditions withoutmodification. Stomatal behavior was optimal at different leafages and under different degrees of water stress.
Acknowledgments
This research was supported by the U.S. Department of Energy’s Ter-restrial Carbon Program and the California Agricultural ExperimentStation. We thank Drs. Joon Kim and Eva Falge for valuable com-ments on the manuscript. Nancy Kiang and Jianwu Tang assisted inmaking the predawn water potential measurements. We also thankMr. Russell Tonzi for use of his ranch and Todd Dawson and the mem-bers of his lab for help with leaf nitrogen measurements.
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