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a USDA-ARS, Agron. Dep., Univ. of Florida, Gainesville, FL 32611
b Agron. Dep., Univ. of Florida, Gainesville, FL 32611
c Agric. and Biol. Eng. Dep., Univ. of Florida, Gainesville, FL 32611
* Corresponding author (LAllen{at}gainesville.usda.ufl.edu)
Received for publication November 28, 2001.
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ABSTRACT |
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 TOPNOTES ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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Abbreviations: CER, carbon dioxide exchange rate • D, air vapor pressure deficit • DAP, days after planting • EST, eastern standard time • ET, evapotranspiration • LAI, leaf area index • PAR, photosynthetically active radiation • Rc, canopy resistance • SPAR, Soil–Plant–Atmosphere research • TOD, time of day • WUE, water use efficiency
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INTRODUCTION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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Stomatal conductance is decreased by elevated CO2 concentration, and leaf transpiration rate is therefore decreased (Bunce, 1998; 2000; Jarvis et al., 1999; Griffin and Luo, 1999; Morison, 2001). Although transpiration rates of individual leaves are decreased about 40% by doubled CO2 concentration, plant community transpiration rates are less affected (Allen, 1999). Soybean canopies grown at 660 µmol CO2 mol-1 transpired about 10% less water over the season than canopies at 330 µmol CO2 mol-1 (Jones et al., 1985c). Although doubled CO2 decreased leaf transpiration rate of big bluestem (Andropogon gerardii Vitman) by 25 and 35% under high- and low-water treatments, respectively, average canopy water use was decreased less, by 15 and 7%, respectively (Kirkham et al., 1991). Elevated CO2 increased WUE of soybean (Jones et al., 1985b, 1985d) and rice (Oryza sativa L.) (Baker et al., 1990). Jones et al. (1985a) found that daily soybean transpiration increased about 4 to 5% °C-1 across a temperature range of 28 to 35°C. This sensitivity of transpiration to increasing temperature is similar to an average daily total ET increase of 6.7% °C-1 predicted by Rosenberg et al. (1990) for vegetation using a Penman–Monteith model.
Most of the earlier research on the effect of temperature on transpiration was conducted under normal to moderately high temperature or for short-term exposures rather than season-long exposures with very high temperatures. The purpose of the present study was to determine the effect of doubled CO2 and a wide range of elevated temperatures (representing temperature increases that not only include but also exceed those anticipated by global warming predictions) on soybean foliage temperature, foliage-to-air temperature and vapor pressure differences, leaf and canopy resistances, and canopy ET and WUE. Our hypothesis was that effects of elevated temperatures on canopy ET could override the water savings effect expected from elevated CO2.
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MATERIALS AND METHODS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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An aluminum frame that supported clear polyethylene telephtalate film (SIXLIGHT, Taiyo Kogyo Co., Tokyo, Japan) formed the walls of each SPAR chamber. The chambers were originally 1.0 m (north–south) by 2.0 m (east–west) in cross section, with an average height of 1.5 m. A 1.2-m3 volume was added on the south side with a trap door at the bottom that allowed a person to stand outside while working inside. A drawstring body seal prevented air exchange, and a face-cover breathing apparatus prevented contamination of the chamber with CO2.
These SPAR chambers transmitted an average of 88% of the incoming photosynthetically active radiation (PAR). The PAR above the chambers was measured continuously with a LI-COR Model LI-190SA quantum sensor (LI-COR, Lincoln, NE). The modified chambers had an aerial volume of 4.4 m3, with an air exchange rate of 2.7 chamber volumes per minute. A chilled-water system operating at about 4 to 8°C provided controlled water flow to cooling coils (heat exchangers) in external ductwork for dew point temperature control. Humidity was removed from the air by condensation on the cooling coils. The air was restored to the desired dry bulb temperature by a regulated electrical resistance heater. Dew point temperature was measured by a dew point hygrometer (Model Dew-10, General Eastern, Watertown, MA) just before the air was returned to the chamber. Air temperature was measured with a radiation-shielded, aspirated, copper-constantan thermocouple suspended above the plant canopy. Foliage temperature was measured with infrared radiation thermometers (Model 4000.4GL, Everest Interscience, Tucson, AZ) with a 15-degree angle of view mounted near the top of the chambers.
Carbon dioxide concentration of each chamber was measured with a gas analyzer (Model Ultramat 21P, Siemens, Apharetta, GA), and set point concentration was maintained by injecting CO2 through a mass flow controller (Model 5850i, Brooks Instruments, Hatfield, PA). A leakage test gas, N2O, was injected at 1000 and 1400 h eastern standard time (EST) each day and at hourly intervals each night.
The controller–data acquisition system consisted of a PC host processor interfaced with subprocessors at each SPAR chamber. Programs for logging data and environmental control were downloaded from the host processor to each subprocessor (Model CR-10T, Campbell Scientific, Logan, UT) under the aegis of a Real Time Monitoring System (Campbell Scientific, Logan, UT). The subprocessors recorded air temperature, dew point temperature, and CO2 concentration at frequent intervals (<10 s) and actuated devices for control of dew point temperature, air temperature, and CO2 concentration. Carbon dioxide exchange rate (CER) was calculated every 5 min (Pan, 1996). Likewise, transpiration rates were calculated every 5 min from condensate draining through tipping-bucket rain gauges. The chambers were vented for 15 min each hour at night and then closed for measuring dark respiration rates by the method of Baker et al. (2000). Thus, CO2 was not controlled at night. Corrections of SPAR chamber leakage were described in Pan (1996) based on Jones et al. (1984b). More SPAR chamber details were described by Allen et al. (1994) and Pickering et al. (1994).
Environmental Treatments
Experiments were conducted on soybean (cv. Bragg) from seeding to maturity at the University of Florida in the fall of 1993 and the spring of 1994. In 1993, plants were grown in eight chambers to two concentrations of CO2, 350 or 700 µmol mol-1, and to cyclic maximum/minimum air temperatures of 28/18°C, 32/22, 36/26, or 40/30°C. To extend the high temperature range to the physiological limit of soybean, in 1994, plants were grown at cyclic maximum–minimum air temperatures of 28/18, 32/22, 36/26, 40/30, 44/34, and 48/38°C at 700 µmol CO2 mol-1 and to 28/18 and 40/30°C at 350 µmol CO2 mol-1 (Fig. 1A). The temperature cycle was sinusoidal from 0700 h EST (the minimum temperature) until 1800 h EST, with the maximum at 1500 h EST. A decreasing exponential function determined the set point temperature from 1800 h EST until 0700 h EST the next day (Fig. 1A). Dew point temperatures were controlled to values of 12/10, 16/12, 20/14, 24/16, 28/28, and 32/20°C for the corresponding six levels of temperature control, which provided the daytime (0800 to 1800 h EST) chamber Ds shown in Fig. 1B. These controlled environments provided nearly constant relative humidities (40–42%) at 1500 h EST. Under global warming scenarios, atmospheric general circulation models predict that specific humidities would increase but that relative humidities would stay somewhat constant (Rind, 1998). The deviations between measured chamber air temperatures from the set point temperatures were about ±0.2°C. The deviations of measured SPAR chamber CO2 concentrations from the set point concentrations were around ± 0.5 µmol mol-1 for both 350 and 700 µmol CO2 mol-1 treatments. The source of most of the evaporated water was from foliage rather than soil evaporation. The subirrigation system supplied root water needs effectively, but the soil surface remained dry except for slight dampness at senescence.
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Vapor Pressure
Saturation vapor pressure dependence on temperature was calculated using the formula of Murray (1967). Saturated vapor pressure and actual vapor pressure were calculated from the chamber dry bulb temperature and dew point temperature, respectively. Vapor pressure in the leaf was calculated as saturated vapor pressure at the foliage temperature measured by the infrared radiation thermometers. The D between the saturated vapor pressure of SPAR chamber air and actual vapor pressure of the air at the existing temperature was calculated as the difference between saturated vapor pressure and actual vapor pressure (Fig. 1B). The vapor pressure difference from inside to outside of the leaf was calculated as the difference between vapor pressure in the leaf and actual vapor pressure.
The choice of chamber air temperature and dew point temperature controls for this experiment (Pickering et al., 1994) resulted in a nearly linear relationship between average D (during the 0800- to 1800-h period) and air temperature. The regression equation was D = 2.026 + 0.1695 x Tair (r2 = 0.99), where Tair is the mean treatment air temperature, or D = 2.874 = 0.1695 x Tair (r2 = 0.99), where Tair is the maximum treatment air temperature.
Leaf Stomatal Conductance and Canopy Resistance
A LI-COR Model 6200 portable photosynthesis system was used to measure stomatal conductance (LI-COR, Lincoln, NE). Measurements were made at the CO2 and temperature treatment levels inside the SPAR chambers at midday during high PAR flux densities.
The equation of Monteith and Unsworth (1990) was used to calculate Rc (s m-1):
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is air density at air temperature (mmol m-3), Mw and Ma are the molecular weights of water vapor and air, respectively; P is atmospheric pressure (Pa); VPleaf is vapor pressure in the leaf (Pa); and VPair is actual vapor pressure (Pa).
Evapotranspiration
Evapotranspiration condensate that passed through the tipping-bucket rain gauge was collected in 40-L plastic vessels that were weighed daily. The amount of water per tip was calibrated from total daily water weight divided by the number of tips accumulated during the same time interval. The ET rate was calculated as the number of tips per 5-min interval recorded by the computer system multiplied by the moles of water per tip.
Water Use Efficiency
Water use efficiency was calculated as the canopy CER (µmol CO2 m-2 s-1) divided by the canopy ET rate (mmol H2O m-2 s-1) over the same time interval, i.e., WUE = CER/ET, with WUE expressed as µmol CO2 mmol-1 H2O.
Data Selection and Statistical Analysis
Data at 35 DAP (after sufficient ground cover was obtained) were selected for analysis of treatment effects on the diurnal course of Rc, ET, and WUE. Twenty-five dates were selected for whole-day analyses of ET and WUE to demonstrate the seasonal progression of plant responses under the various treatments. No dates before 20 DAP were selected because of insufficient leaf area for intercepting radiation for measurements of ET and (Pan, 1996) for calculating WUE. No dates after 95 DAP were selected because of the onset of leaf senescence. A number of other dates were not selected because the chambers were opened for short periods of time sequentially during the day either to conduct plant sampling or to tag plants and make observations on vegetative or reproductive development (Pan, 1996). Other dates were eliminated because of low or excessively variable solar irradiance. Finally, a few days were eliminated because of some type of failure of data-recording equipment on one or more chambers. Twelve of the 25 d with steady solar irradiance during the midday measurement period were selected for calculation of midday Rc.
Regression (PROC STEPWISE) procedures using the stepwise option in the model statement as described in the SAS User's Guide: Statistics (SAS Inst., 1987) were used for data analyses. For the effects of temperature on daily cycles of Rc, ET, and WUE at 35 DAP, the independent variables were time of day (TOD), temperature (TEMP), TOD2, TEMP2, and TOD x TEMP of the five temperature treatments (44/34, 40/30, 36/26, 32/22, and 28/18°C) at 700 µmol CO2 mol-1. Data of Rc, ET, WUE, and LAI on the selected dates across the growing season were analyzed in a similar manner but with DAP used rather than TOD.
Effects of the combination of CO2 (350 and 700 µmol CO2 mol-1) and temperature (40/30 and 28/18°C) on Rc, ET, and WUE were analyzed stepwise as above with independent variables of CO2, TEMP, TOD (or DAP), TOD2 (or DAP2), and interactions of CO2 x TEMP, TOD x TEMP (or DAP x TEMP), and CO2 x TOD (or CO2 x DAP). In addition, the independent variable TOD3 was added to the analysis of WUE over the diurnal period at 35 DAP because the shape of the response curve was concave upward early in the day and concave downward late in the day. The maximum values of the daily maximum–minimum temperatures were used for the TEMP independent variable. The effect of the combination of CO2 and temperature, along with DAP, on LAI was analyzed in a similar manner. Finally, simple linear regressions were also conducted on some of the summarized data as explained in the Results and Discussion. Because of the linear dependence of mean daytime D (0800 to 1800 h) on TEMP under the conditions of this experiment, D was not used as a dependent variable in these statistical analyses.
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RESULTS AND DISCUSSION |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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Leaf Area
During the first 39 DAP of the 1994 study, LAI increased most rapidly for the 36/26°C temperature treatment and increased less rapidly in order of 40/30, 44/34, 32/22, and 28/18°C (Table 1). The LAI of the 44/34°C treatment continued to increase until 71 DAP. The ranking order for LAI from 53 DAP until the end of the experiment for the 700 µmol CO2 mol-1 treatment was 44/34, 40/30, 36/26, 32/22, and 28/18°C. Regression of LAI vs. TEMP and DAP at 700 µmol CO2 mol-1 (from 11–85 DAP) was significant (R2 = 0.91, P < 0.0001) (Table 2, Line 7). The CO2 concentration effect on midseason LAI was small at 40/30°C, but the midseason LAI was about 50% greater at high CO2 for 28/18°C (Table 1). Regression of LAI vs. CO2, TEMP, and DAP (from 11–85 DAP) was also significant (R2 = 0.91, P < 0.0001) (Table 2, Line 14). However, the CO2 effect and the CO2 x TEMP interaction were not significant at the 0.05 level. Therefore, regression of midseason (from 39–85 DAP) LAI vs. CO2, TEMP, and DAP was conducted (R2 = 0.94, P < 0.0001). Both the CO2 effect (P = 0.0035) and CO2 x TEMP interaction (P = 0.0128) were significant for the midseason LAI data (Table 2, Line 14-A).
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Leaf and Canopy Resistance
Stomatal conductance measurements at high PAR were positively correlated with leaf temperatures and negatively correlated with CO2 concentrations, and interaction of temperature and CO2 was not significant. The relationship for the soybean leaf stomatal conductance (gs) across the leaf temperature (Tleaf ) range of 27 to 41°C and CO2 concentrations of 350 and 700 µmol mol-1 was gs = -0.369 + 0.041 x Tleaf - 0.00052 x CO2. Based on this relationship, the CO2–induced decrease in leaf conductance was 33% at 27°C and 17% at 40°C. Leaf resistances were calculated using this equation, which showed that the ratio of leaf resistance for 700 vs. 350 µmol CO2 mol-1 increased 48% at 27°C and 20% at 40°C. Thus, the effect of elevated CO2 on stomata was much less at higher temperatures. Cure (1985) and Cure and Acock (1986) reviewed 21 experiments and computed a decrease of 31 ± 5% in stomatal conductance (45% increase in stomatal resistance) of soybean for a doubling of CO2 concentration, but most of these studies were conducted at temperatures much lower than 40°C and closer to 27°C. Morison (1987) reviewed 23 reports with different species and found a 40 ± 5% decrease in stomatal conductance (66% increase in stomatal resistance) at 660 compared with 330 µmol CO2 mol-1. Thus, doubled CO2 increased stomatal resistance almost 50% at normal temperature although results in this study indicate less effect at elevated temperature.
Regression of Rc to water vapor loss during the daily cycle at 35 DAP was significantly affected by linear, quadratic, and interaction terms of TOD and TEMP (R2 = 0.92, P < 0.0001) (Table 2, Line 1). Canopy resistance was lower at higher treatment temperatures (Fig. 3A). Canopy resistance was also affected by PAR because it is a major driving force for water loss, for stomatal function, and for photosynthesis to draw down leaf intercellular CO2 concentration and thereby affect stomatal guard cell function. Part of the diurnal response of Rc must also be attributed to diurnal changes in temperature (and PAR) because lowest resistance occurred near 1500 h EST when temperature peaked (130 s m-1 under 28/18°C conditions down to 50 s m-1 under 44/34°C conditions). Regression of Rc vs. CO2, TEMP, and TOD at 35 DAP was significant (R2 = 0.93, P < 0.0001 for all independent variables and interactions except CO2 x TOD) (Table 2, Line 8; Fig. 3B).
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Evapotranspiration
Instantaneous ET rate followed a diurnal cycle (Fig. 5), which peaked about 2 h after peak solar irradiance. This peak in ET was associated with peak temperature (and peak D) of the diurnal temperature treatment cycle similar to field data reported by Pruitt (1964). The maximum midday ET also increased with temperature from about 7.5 mmol H2O m-2 s-1 at 28/18°C to 17.5 at 40/30°C and 19.0 at 44/34°C (Fig. 5A). Stepwise regression of ET vs. TOD and TEMP at 35 DAP was significant (R2 = 0.94 and P < 0.0001 for overall regression and for each independent variable) (Table 2, Line 2). Both incoming solar radiation and heat inputs for controlling air temperatures of the chambers were energy sources for evaporation from the leaves. Elevated CO2 caused lower ET for the 28/18°C treatments, but the effect of elevated CO2 on ET was less at 40/30°C treatment (Fig. 5B). Regression of ET vs. CO2, TEMP, and TOD at 35 DAP was significant (R2 = 0.90 and P < 0.0001 overall and for each independent variable and interaction except CO2 x TOD) (Table 2, Line 9).
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In an attempt to partition the TEMP effects and the LAI effects on ET, a regression of ET vs. LAI, TEMP, DAP, and DAP2 was conducted. The parameter estimate for LAI was 40 mmol H2O m-2 d-1 LAI-1, and the parameter estimate for TEMP was 14 mmol H2O m-2 d-1 °C-1. The range of temperature treatments was always 16°C, regardless of DAP, whereas the typical range of LAI values within a given DAP during the season was about 4. The predicted range of responses to TEMP would be 14 x 16 = 224 mmol H2O m-2 d-1, and the predicted range of responses to LAI would be 40 x 4 = 160 mmol H2O m-2 d-1. The value of the ratio provides an estimate that ET was about 1.4 times more sensitive to the TEMP variable as it was to the LAI variable. However, LAI is a function of TEMP, so this analysis is confounded.
The ratio of ET/LAI vs. LAI showed a slope of -5.3 mmol H2O m-2 d-1 LAI-2, but the correlation coefficient was low (0.24), which indicated that there was considerable variability of the data set among TEMP and CO2 treatments and growth stages of development and senescence (DAP).
Regression of total daytime ET vs. CO2, TEMP, and TOD was significant (R2 = 0.90 and P < 0.0001 overall and for components shown in Table 2, Line 12). At 28/18°C, although LAI in doubled CO2 was higher than that in the ambient CO2 treatment, canopy transpiration rate was lower (Fig. 6B). Cure (1985) and Cure and Acock (1986) calculated a 23% decrease of leaf transpiration under doubled CO2 conditions based on 19 reports for soybean. Kimball and Idso (1983) extracted 46 observations of various plants and found an average reduction in transpiration of 34 ± 17% (range of 8–68%) with doubling of CO2. For the 28/18°C temperature, the decrease of soybean canopy ET with doubled CO2 over the 25 d illustrated in Fig. 6B was 9%. This decrease is considerably less than leaf-level values reported by Cure (1985), but it is similar to decreases of canopy-level ET rates with doubled CO2 reported by Jones et al. (1984a)(1985b, 1985c, 1985d) and by Allen et al. (1985). Data obtained by averaging total ET for the 25 d in 1994 (Fig. 6B) showed that there was much less CO2 effect on ET at 40/30°C.
The 25-d mean of daily ET (mol H2O m-2 d-1) including all data of Fig. 6A and 6B (both CO2 concentrations) was linearly related to chamber air temperature (Tair, °C) over the five mean daily treatments ranging from 23 to 39°C (ET = -306 + 21.4 x Tair; r2 = 0.99). The 25-d mean of daily ET was also linearly related to SPAR chamber D (ET = -44.98 + 124.6 x D; r2 = 0.99). Vapor pressure deficit acted as the primary determinant of ET. When the 25-d mean of daily ET was normalized by average chamber D, daily ET (mol H2O m-2 d-1 kPa-1) was 112, 114, 114, 103, and 100 for the 44/34, 40/30, 36/26, 32/22, and 28/18°C treatments, respectively, at 700 mol CO2 mol-1 and 114 and 109 for the 40/30 and 28/18°C treatments, respectively, at 350 mol CO2 mol-1. Thus, ET/D was relatively constant, as theory suggests (Tanner and Sinclair, 1983).
In the midrange of these air temperatures (30–35°C), daily total ET will increase about 6.4% °C-1. This sensitivity to temperature increase is very close to the weighted average daily total ET increase of 6.7% °C-1 predicted by Rosenberg et al. (1990) using a Penman–Monteith model. The weighted average ET increase was based on 23 daily simulations of ET for a 3°C increase in temperature over three types of vegetation systems (Tables 7.2, 7.3, and 7.4 in Rosenberg et al., 1990) under various weather conditions. The daily total ET predicted by this model was linearly related to change in air temperature (increase or decrease) from a baseline value (Fig. 7.1 in Rosenberg et al., 1990). For a combination of possible climate change factors (+3°C, +10% net radiation, +10% vapor pressure, +40% stomatal resistance, and +15% LAI), the ensemble weighted average simulations of ET increased about 4.0% °C-1. Part of the reason for the smaller predicted change of ET for the combination of factors might be the lack of energy balance feedback that would ameliorate the impact of increasing stomatal resistance.
The extent of the decrease of ET by CO2 appeared to be reduced by the effect of elevated leaf temperature. This experiment confirmed conclusions based on sparser data by Allen et al. (1985) and Allen (1990)(1991, 1999), who suggested that both increased crop LAI and especially increased foliage temperature at doubled CO2 tended to offset reductions in crop transpiration that might be expected from elevated CO2. If global temperature rises with increasing CO2, crop water use may actually increase.
Water Use Efficiency
Instantaneous WUE at 35 DAP decreased with TOD and TEMP for all treatments (Fig. 7A). Regression analysis of WUE vs. TOD and TEMP was significant (R2 = 0.94 and P < 0.0001 overall and TOD, TEMP, TEMP2, and TOD x TEMP interaction) (Table 2, Line 3). Because of the shape of the plotted data in Fig. 7A, TOD3 was included, but it was not called in the stepwise regression. In the morning, gross photosynthesis (Pan 1996) and ET both increased as the sun was rising, but the increase in ET was greater than that of photosynthesis. In the afternoon, photosynthesis decreased as the PAR decreased, but SPAR chamber air temperatures and D were still relatively high (the maximum diurnal temperature was set at 1500 h EST); therefore, ET did not decrease as soon as photosynthesis, and WUE kept decreasing. This effect is also seen in field experiments (Zur and Jones, 1984).
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Although the 36/26 and 40/30°C treatments had the highest canopy photosynthetic rate (Pan, 1996), their seasonal ET was much higher than that of the lower temperature treatments (Fig. 6). Therefore, seasonal WUE at 36/26 and 40/30°C was lower than that at 32/22 and 28/18°C; thus, daily WUE decreased as the treatment temperature increased (Fig. 8A). Regression analysis showed that daily WUE vs. DAP, first- and second-degree TEMP, and DAP x TEMP interaction was significant (R2 = 0.93 and P < 0.0001, Table 2, Line 6). Doubled CO2 caused higher canopy photosynthesis and therefore resulted in higher seasonal WUE compared with ambient CO2 treatments (Fig. 8B). Linear regression analyses of daily WUE vs. CO2, DAP, and TEMP and all interactions were significant (R2 = 0.95, P < 0.0001, Table 2, Line 13). When the WUE was averaged over 25 dates for each temperature treatment of plants grown at 700 µmol CO2 mol-1, daily mean WUE decreased linearly with temperature treatment. The relationship of mean WUE (mmol CO2 mol-1 H2O) vs. mean temperature (Tair, °C) was WUE = 7.50 - 0.150 x Tair (r2 = 0.95), and the relationship of mean WUE vs. mean D (kPa) was WUE = 5.67 - 0.874 x vapor pressure difference (r2 = 0.95), with plots of data not shown. The WUE was about 1.5 or 1.6 greater in high-CO2–grown plants compared with low-CO2–grown plants for 28/18°C or 40/30°C treatments, respectively. This canopy WUE increase was lower than the value of 2.5 reported for individual leaves (Allen et al., 1994).
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SUMMARY AND CONCLUSIONS |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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ACKNOWLEDGMENTS |
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NOTES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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REFERENCES |
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TOPNOTESABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTS AND DISCUSSIONSUMMARY AND CONCLUSIONSREFERENCES |
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