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Evaluation of an ozone × moisture stress interaction model for soybean
Ecological Modellin~ 41 (1988) 269-279 Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands
EVALUATION OF AN OZONE × MOISTURE
269
STRESS INTERACTION
M O D E L FOR S O Y B E A N
DAVID A. KING 1, ALLEN S. HEAGLE 2 and RICHARD B. FLAGLER 3
1 Department of Physical and Life Sciences, University of Portland, Portland, OR 97203 (U.S.A.) 2 U.S. Department of Agriculture, Agricultural Research Service, Plant Pathology Department, North Carolina State University, Raleigh, NC 27650 (U.S.A.) 3 Department of Crop Science, North Carolina State University, Raleigh, NC 27695-7630 (U.S.A.) (Accepted 22 September 1987)
ABSTRACT King, D.A., Heagle, A.S. and Flagler, R.B., 1988. Evaluation of an ozone × moisture stress interaction model for soybean. Ecol. Modelling, 41: 269-279. Assessments of air pollution impacts on crops may overestimate losses because they do not consider the impacts of soil moisture deficits on pollutant uptake by plants. A recent model of moisture stress × ozone interactions predicted reduced ozone (O3) impacts on yields of drought-stressed crops, due in part to an assumed reduction in the accumulation of 03 damage during drought. This paper describes an evaluation of the model with 03 × moisture stress field experiments on soybean conducted at Raleigh, NC, U.S.A. Modelled yield losses due to 03 were smaller than observed for moisture-stressed soybean, but these differences were not statistically significant. The model predictions were consistent with the 03 × H20 interaction observed by other researchers for soybean grown in a controlled environment.
INTRODUCTION O z o n e e x p o s u r e e x p e r i m e n t s have b e e n c o n d u c t e d o n a n u m b e r o f econ o m i c a l l y i m p o r t a n t c r o p s b y the N a t i o n a l C r o p L o s s A s s e s s m e n t N e t w o r k ( N C L A N ) to assess the effects o f o z o n e ( 0 3 ) o n the agricultural e c o n o m y o f the U.S.A. ( A d a m s et al., 1984). T h e s e assessments c o n c l u d e that a m b i e n t 0 3 levels s u b s t a n t i a l l y r e d u c e c r o p yields across large regions ( A d a m s et al.,
Reprint requests should be sent to: David King, Corvallis Environmental Research Laboratory, U.S. Environmental Protection Agency, 200 S.W. 35th Street, Corvallis, OR 97333, U.S.A. 0304-3800/88/$03.50
© 1988 Elsevier Science Publishers B.V.
270 1984; Heck et al., 1984). However, most of the field experiments used to estimate 03 effects have been conducted on adequately watered plants. Moisture stress caused by soil moisture deficits can reduce the occurrence of 03 injury symptoms by inducing stomatal closure (Dean and Davis, 1967; Tingey et al., 1982) and may also reduce 03 impacts on yield. Hence, assessments based on experiments with well-watered plants may overestimate losses caused by 03 . To evaluate the impact of soil moisture deficits on 03 damage to crops, N C L A N researchers have conducted moisture stress x 03 field exposure experiments, and constructed a crop simulation model to predict drought x O 3 interactions across geographic regions. The simulation model was applied to soybean, because this crop is sensitive to 03 and of great economic value (2nd to corn in the U.S.) (Adams et al., 1984). The model incorporates plant responses to moisture stress and 03 reported in the literature, but has not yet been tested against NCLAN experiments. This paper describes a test of the model using inputs from soybean moisture stress x 03 experiments conducted at Raleigh, NC. Because the object of interest is the potential shift in 03 effects on yield due to drought, the model was first calibrated for well-watered soybean and then run with water inputs from the water-stressed treatments. Comparison of modelled vs. observed water-stressed yields indicates the adequacy of the model. THE MODEL Plant uptake of CO 2 and 03, and loss of H20 through transpiration are all highly correlated because all three processes are mediated by the opening and closing of stomata. Transpiration plays a central role in the above processes because it influences soil water content which in turn affects stomatal behavior. Hence, transpiration was chosen as the central variable in modelling the 03 X moisture stress interaction. A complete description of the model is provided by King (1987). In the following section, we outline the general approach and specify those relationships involved in calibrating the model to the experimental data set. The model simulates soil moisture status and crop transpiration throughout the season, given daily inputs of rainfall and pan evaporation and hourly O 3 concentrations. Transpiration is calculated from pan evaporation for each day as modified by crop growth stage, cumulative 03 exposure, and soil water content of the previous day. Soil water content is then updated by balancing daily rainfall inputs against losses due to drainage and evapotranspiration. Soil water is assumed to limit transpiration when plant available water in the rooting zone falls below 1/2 of the potential available water at field capacity (Hanks, 1974; King, 1987).
271 The computation of 03 effects on transpiration is based on cumulative 03 exposure above a threshold level. For days of adequate soil moisture, the model computes an hourly 03 dose (Dh) as: D h = [03] - Zh, and D h = 0 ,
for for
[03] > T h
[03] < Th
(1)
where [03] is the mean 03 concentration over the hour in question and T h is an hourly mean threshold concentration which must be exceeded before any effects are expected. The daily dose (D i) is defined as the sum of the hourly dose over the daylight hours when stomata are likely to be open, i.e.
Di---EDh
(2)
03 exposure is assumed to cause a linear decline in transpiration as reported by Reich et al. (1985). This effect is modelled by computing a transpiration reduction factor:
Fi = E'-I "[- kOl
(3)
where F~_ 1 is the value of the factor on the previous day, and k is a constant denoting the sensitivity of transpiration to the 03 dose; F~ = 0 for the day of crop emergence and increases over the season with cumulative 03 exposure. The transpiration reduction factor is then used to calculate daily transpiration (T) for an O3-exposed crop relative to that of an unexposed crop (To) as: T / T o = 1 - F~
(4)
The mechanics of the model restrict F~ to values less than 1 so that the ratio T / T o lies between 0 and 1. Moisture stress impacts on the 03 effect are incorporated into the above calculation by decreasing the 03 dose of equations (1) and (2) on those days when soil moisture deficits limit transpiration (King, 1987). Specifically:
O h = ( T / T p ) TM [ 0 3 ] -
Th,
for
{(T/Tp) TM [O3]) > T h
and Dh=0,
for
{(T/Tp) TM [O31 } < rh
(5)
where Tp is the potential transpiration expected for a crop not impacted by soil moisture stress or 03 , and T is the transpiration predicted for a crop impacted by both of these stresses; values of T and Tp for the i - l t h day are used to compute the Dh's and D~ for the ith day, i.e., the model increments all variables based on their previous day's values and on the current day's water inputs, pan evaporation, and hourly 03 concentrations.
272 Thus, the modelled decrease in transpiration caused by O 3 damage increases as the season progresses, but the rate of accumulation of 03 effects is reduced during periods of soil moisture deficit. An additional interaction arises from the decrease in transpiration caused by 03 damage which results in less soil water depletion in O3-exposed crops. The estimated daily transpiration is summed over the growing season to define the total seasonal transpiration (ST). This estimate of ST is then multiplied by the transpiration efficiency (TE) to predict yield: TE denotes the yield per unit of water transpired. For this model, TE is assumed to be unaffected by moisture stress, but reduced by cumulative 03 exposure, as described by King (1987). By running the model for a range of O 3 and irrigation scenarios, one can predict how moisture stress should alter the yield response to 03 . METHODS
Experiments The field studies used to test the model were conducted at the U S D A - N o r t h Carolina State University Air Quality Field Research Laboratory, 9 km south of Raleigh, NC, U.S.A., in 1983 and 1984 (Flagler, 1986; Heagle et al., 1985, 1986, 1987). Open-top chambers (Heagle et al., 1973) were used to expose field-grown soybean to charcoal-filtered air (CF), nonfiltered air (NF), and N F air with different amounts of added 03 using methods described previously (Heagle et al., 1979). The experiments involved four 03 levels × two moisture treatments in 1983 and six 03 levels x two moisture treatments in 1984. Three and two replicates per 03 x moisture treatment were employed in 1983 and 1984, respectively. Details are summarized in Table 1. The soybeans were grown in a 28-cm deep layer of Norfolk loamy sand topsoil overlaying Appling sandy loam with approximately 20 cm of topsoil. Potential plant-available soil water (PSW) was only 1.9 cm for the Norfolk topsoil and about 2 cm for the Appling topsoil. Neutron probe estimates of soil moisture indicated only a small decline in soil moisture at 45-cm depth over the growing season. Hence, the rooting zone was taken to consist of only the above two layers and PSW was set at 4 cm for the model simulations. The two experimental moisture treatments, established by different irrigation frequencies, were well-watered (WW) and water-stressed (WS). The WW plots received 2.5 cm of water by drip tubing whenever soil water potential (~ks) dropped to - 0 . 0 3 MPa in any of the replicates of a given 03 treatment. The WS plots received 2.5-cm irrigations when leaf water potentials reached - 1 . 8 MPa (1983) or ~ks reached 0.5 MPa (1984) (Flagler,
273 TABLE 1 Description of soybean experiments used to test the model Cultivar: Davis Plant spacing: 19 plants per m of row (after thinning), 1.0 m between rows a Method of exposure: Constant additions of ozone to nonfiltered air from 9:00-16:00 EST, plus nonfiltered and carbon-filtered treatments Moisture stress: Two treatments, one maintaining adequate soil moisture, the other producing soil moisture deficits after mid-season (early August) Event
Planting Begin dispensing 03 First flower Begin pod fill End of flowering Physiological maturity Last day of 03 addition Final harvest
Date 1983
1984
16 June 7 July 10 August 4 September 13 September 15 October 24 October 9, 14 November
11 June 7 July 10 August 5 September 15 September 17 October 18 October 6 November
a Original stand 0.5 m, but thinned to 1.0 m row spacing by removing center row (5 plants at a time).
1986). Daily ~ks was monitored by one tensiometer per chamber, at a depth of 20 cm. Neutron probe estimates of ~Ps, taken at weekly intervals from a 22-cm depth, were used to schedule irrigations for the WS plots in 1984. Well-watered plots required a mean seasonal water supplement of 55 cm in 1983 and 26.3 cm in 1984; the 1983 growing season was hotter and drier than the 1984 season (Flagler, 1986). All WS plots received five irrigations on the same dates in both years, except for the two high-O 3 chambers of 1984, which received one less irrigation. One of the CF WS yields was discarded due to poor plant establishment for each year.
Model calibration The model was used to compute the yield of each chamber based on inputs of hourly 03 concentrations and daily water additions for each chamber. Daily pan evaporation values reported by the Weekly Weather and Crop Bulletin for Chapel Hill, NC (40 km NW of the experimental site) were used in the simulations. Potential plant available water (Psw) was increased with crop development in the model formulated by King (1987). Psw was fixed at 4 cm throughout the season in this study, because of the shallow rooting depth inferred for the Raleigh experimental site.
274 The model was originally calibrated to approximate the common soybean O3-response reported by Heck et al. (1983), when run with hourly 03 concentrations reported over daylight hours. However, the 03 impacts predicted for the WW treatments at Raleigh differed from the observed response, due in part to differences between experimental and ambient exposure conditions; the former included 7 - h / d a y 03 additions starting 3-4 weeks after planting. Since the main objective of the study was to test the ability of the model to predict impacts of drought on the crop response to 03, the model was recalibrated to mimic observed 03 effects for the WW treatments of each year. This calibration was accomplished by adjusting the 03 sensitivity parameter (k of equation 3) to minimize the variance between observed and modelled yields for the WW chambers. This parameter was set equal to 0.0165 1/~1 and 0.026 1/~1 for 1983 and 1984, respectively. Simultaneously, the damage threshold (Th of eqn. 1) was raised from the original value of 0.01 I~1/1 to 0.05 l~l/1, to improve the model fit to these WW yields. However, as Th is increased, the calculated ozone depression of transpiration decreases and modelled water use increases. To avoid this shift in water use, potential transpiration was reduced by 15% from that calculated by the original version of the model. Other model parameters were set at the values used by King (1987). The calibrated model was then used to simulate yield for each of the WS chambers. RESULTS Modelled and observed soybean yields are plotted as a function of 03 exposure in Figs. 1 and 2 for 1983 and 1984. Because the model was calibrated to predict the observed mean yield without water stress, a comparison of modelled vs. observed yields for the WS case indicates the accuracy of predicted drought impacts on yield. In both years, the model predicted smaller moisture stress impacts on mean WS yield than were observed, as shown in Table 2. This difference was significant ( P < 0.01) for 1983, but not for 1984. However, these difference were of modest size compared to total drought impacts. In 1983, water stress reduced observed mean yield by 51% while the model predicted a 37% effect. In 1984 the observed and modelled drought impacts were 20% and 16%, respectively. The model also predicted some moisture stress impacts on WW chamber yields, particularly for the charcoal-filtered treatment of 1984 where a 5% yield reduction by moisture stress was predicted. However, the magnitude of this prediction is uncertain because of possible errors in predicted evapotranspiration and the estimate of potential available soil moisture. The model predicted reduced sensitivity to 03 with moisture stress (Figs. 1 and 2), consistent with the model predictions presented by King (1987). The
275
500
400
j" 300 ED -J UJ
.............................
"(9".............
>ED
O
200
8
o
UJ UJ O9
8
oo
o I00
I
0
002
MEAN
I
I
I
t
004
006
008
0~0
0 ~2
7-H/DAY SEASONAL [03] (ppm)
Fig. 1. Soybean per-chamber, Raleigh, NC, 1983. Closed (e) and open ( o ) circles indicate well-watered (WW) and water-stressed (WS) treatments, respectively. The solid line denotes WW yields predicted by the model which was calibrated to fit the WW experimental data; the dotted line indicates the WS yields projected by the calibrated model. Seed yield was adjusted to a 13% water content and mean seasonal [03] was computed for 9:00-16:00 Eastern Standard Time over the exposure period.
nonlinear decline in WS yield predicted for 1984 was due in part to plants in the high-O 3 chambers receiving one less irrigation that year. The tendency for the observed values to fall below the modeled values for the higher WS 03 treatments of 1984 (Fig. 2) suggests a bias in the model prediction of the O 3 × H 2 0 interaction. However, an analysis of variance of the difference
500
% 400 ¢u •
¢m
300
O
O
6" ....................
ED _J uJ >E3
•
• 0 o
..... ~ - 3 •~
....... "'"...
o
o o
200
"GL •
UJ uJ 03 100
0
002
MEAN
0 0' 4
0 0'6
0.'10
0 0 '8
7-H/DAY SEASONAL
[03]
012
(ppm)
Fig. 2. Soybean yield per-chamber, Raleigh, NC, 1984. Symbols are defined in Fig. 1.
276 TABLE 2 Observed and modelled soybean yield per water stress treatment for well-watered (WW) and water-stressed (WS) treatments Treatment
Mean observed yield (g/m 2)
Mean modelled yield (g/m 2)
1983 WW 1983 WS 1984 WW 1984 WS
391.0 + 14.8 a 191.4 + 13.5 317.2+ 9.7 248.6 + 13.8
391.0 + 0.9 245.3 + 0.6 317.2+1.3 265.4 + 0.8
a + SE; standard errors were computed from mean square error per O3 × H20 treatment for the observed and modelled means. The difference between WW and WS yields was significar.tly greater for the observed than the modelled case for 1983 (P < 0.01).
TABLE 3 Analysis of variance mean squares for observed minus modelled yield of water-stressed soybean exposed to four levels of 03 in 1983 and six levels in 1984 Treatment
Source of variance
df
Mean squares of observed minus modelled yield
F value
Pr > F
1983 WS
03 Error 03 Error
3 7 5 5
2103 2008 1576 2086
1.05
0.5
0.76
0.5
1984 WS
The error was calculated from the within-O3-treatment variance of (observed-modelled yield). The error does not include model calibration error caused by experimental error in the well-watered yield values used to calibrate the model
b e t w e e n o b s e r v e d a n d m o d e l l e d W S yield i n d i c a t e d n o significant 0 3 effect o n this quantity, as s h o w n in T a b l e 3. T h e difference b e t w e e n o b s e r v e d a n d m o d e l l e d W S yield was negatively c o r r e l a t e d with 0 3 level, b u t n o t signific a n t l y so (r--- - 0 . 1 2 , 1983; r = - 0 . 3 8 , 1984). N o n e t h e l e s s , this t r e n d suggests that the m o d e l m i g h t u n d e r e s t i m a t e c r o p sensitivity to 0 3 in the presence of m o i s t u r e stress, i.e., the m o d e l overestimates the p r o t e c t a n t effect of m o i s t u r e stress. DISCUSSION O u r analysis did n o t reject the 0 3 × H 2 0 i n t e r a c t i o n p r e d i c t e d b y the m o d e l , b u t the test was weak, d u e to substantial e x p e r i m e n t a l variation. N o significant 0 3 × H 2 0 i n t e r a c t i o n was o b s e r v e d for either y e a r ( H e a g l e et al., 1985, 1986, 1987), so a m o d e l w h i c h p r e d i c t e d n o i n t e r a c t i o n w o u l d n o t h a v e
277 50
4O I-z
3o
J
.~ 2o Q
I0
l
o
o.os
I
oo9 [%] (ppm)
I
o.~s
Fig. 3. Aboveground biomass of 50-day old soybean plants exposed to constant 03 levels for 6.8-h/day, as reported by Amundson et al. (1986). The solid and dashed lines indicate well-watered and water-stressed treatments, respectively.
been rejected, either. The difficulty in testing the model has several sources. First, the impact of moisture stress on the O3-response is likely to be smaller than the O3-response itself. Second, including two moisture stress levels halves the number of chambers available to define the exposure response at a given water stress level. Third, any differences in soil moisture holding capacity between plots will increase yield variability with drought stress. Inclusion of higher 03 levels and more replicates would increase the power of experimental tests of the model. A significant O 3 × H 2 0 interaction was observed by A m u n d s o n et al. (1986) in pot-grown soybean. These researchers found that a moisture stress level which halved biomass production, substantially reduced the effect of 03, as illustrated in Fig. 3. Comparison of Figs. 1 and 3 indicates that A m u n d s o n et al.'s interaction was similar to that predicted by the model for severe drought. However, plant age and the indoor exposure system used by A m u n d s o n et al. differed substantially from field conditions. Further experiments are needed to determine if the 03 x H 2 0 interaction is different for field plants than for those in environmentally controlled chambers, before the above results can be taken as confirmation of the model. The model tested here focuses on soil moisture x O 3 interactions and does not consider atmospheric influences on the progression of 03 damage. The calibrated model sensitivity to 03 was 1.6 X greater for 1984 than 1983, suggesting that well-watered soybean was more sensitive to 03 in 1984. The regression slope of relative WS yield vs. [03] was also steeper for 1984 than 1983, although not significantly so. Soybean stomatal conductance and 03 uptake may be influenced by relative humidity a n d / o r vapor pressure deficit
278 (Vr'D), with less 0 3 uptake occurring at low humidity (McLaughlin and Taylor, 1981). This response would explain the above differences in sensitivity, as mean daily pan evaporation (July-September) was 30% greater for the 1983 experiment than for 1984, indicating higher VPD in the former year. California-grown cotton was also less sensitive to 0 3 during a year of high pan evaporation than for a year of low pan evaporation (Temple et al., 1985). Thus, our results do not preclude the possibility that atmospheric conditions may be as important as soil moisture in determining soybean sensitivity to ozone. ACKNOWLEDGEMENTS We thank Karen Randolph, James Reynolds, Luther Smith, and David Tingey for reviewing the manuscript and the National Crop Loss Assessment Network ( N C L A N ) Library for use of soybean chamber yield data. F u n d i n g for this project was provided by the U.S. Environmental Protection Agency under assistance agreement CR-812671 to the University of Portland. The project was administered by the EPA's Environmental Research Laboratory in Corvallis, OR. REFERENCES Adams, R.M., Hamilton, S.A. and McCarl, B.A., 1984. The economic effects of ozone on agriculture. EPA-600/3-84-090, U.S. Environmental Protection Agency, Corvallis, OR, 175 pp. Amundson, R.G., Raba, R.M., Schoettle, A.W. and Reich, P.B., 1986. Response of soybean to low concentrations of ozone: II. Effects on growth, biomass allocation, and flowering.J. Environ. Qual., 15: 161-167. Dean, C.E. and Davis, D.R., 1967. Ozone and soil moisture in relation to the occurrence of weather fleck on Florida cigar-wrapper tobacco in 1966. Plant Dis. Rep., 51: 72-75. Flagler, R.B., 1986. Effects of ozone and water deficit on growth, yield, and nitrogen metabolism of soybeans. Ph.D. dissertation, North Carolina State University, Raleigh, NC, 94 pp. Hanks, R.J., 1974. A model for predicting plant growth as influenced by evaporation and soil water. Agron. J., 66: 660-665. Heagle, A.S., Body, D.E. and Heck, W.W., 1973. An open-top field chamber to assess the impact of air pollution on plants. J. Eviron. Qual., 2: 365-368. Heagle, A.S., Philbeck, R.B., Rogers, H.H. and Letchworth, M.B., 1979. Dispensing and monitoring ozone in open-top fidd chambers for plant effects studies. Phytopathology,69: 15-20. Heagle, A.S., Flagler, R.B., Patterson, R.P., Lesser, V.M., Heck, W.W. and Mowry, F.L., 1985. Influence of soil moisture level on response of soybeans to 03. In: W.W. Heck, O.C. Taylor, R.M. Adams, J.E. Miller, E.M. Preston and L.H. Weinstein (Editors). National Crop Loss Assessment Network (NCLAN) 1983 Annual Report. EPA-600/3-85-061, U.S. Environmental Protection Agency, Corvallis, OR, 227 pp.
279 Heagle, A.S., Flagler, R.B., Heck, W.W., Cure, W.W., Lesser, V.M., Miller, J.E. and Corda, S.L., 1986. Influence of soil moisture on responses of soybean to O3. In: W.W. Heck, O.C. Taylor, R.M. Adams, J.E. Miller, D.T. Tingey and L.H. Weinstein (Editors). National Crop Loss Assessment Network (NCLAN) 1984 Annual Report. EPA-600/3-86-041, U.S. Environmental Protection Agency, Corvallis, OR, 228 pp. Heagle, A.S., Flagler, R.B., Patterson, R.P., Lesser, V.M., Shafer, S.R. and Hock, W.W., 1987. Injury and yield response of soybean to chronic doses of ozone and soil moisture deficit. Crop Sci., 27: 1016-1024. Heck, W.W., Adams, R.M., Cure, W.W., Heagle, A.S., Heggestad, H.E., Kohut, R.J., Kress, L.W., Rawlings, J.O. and Taylor, O.C., 1983. A reassessment of crop loss from ozone. Environ. Sci. Technol., 17: 572A-581A. Hock, W.W., Cure, W.W., Rawlings, J.O., Zaragoza, L.J., Heagle, A.S., Heggestad, H.E., Kohut, R.J., Kress, L.W. and Temple, P.J., 1984. Assessing impacts of ozone on agricultural crops: II. Crop yield functions and alternative exposure statistics. J. Air Pollut. Control Assoc., 34: 810-817. King, D.A., 1987. A model for predicting the influence of moisture stress on crop losses caused by ozone. Ecol. Modelling, 35: 29-44. McLaughlin, S.B. and Taylor, G.E., 1981. Relative humidity: important modifier of pollutant uptake by plants. Science, 211: 167-169. Reich, P.B., Schoettle, A.W. and Amundson, R.G., 1985. Effect of low level of 03, leaf age, and/or water stress of leaf diffusive conductance and water use efficiency in soybean. Physiol. Plant., 63: 58-64. Temple, P.J., Taylor, O.C. and Benoit, L.F., 1985. Cotton yield responses to ozone as mediated by soil moisture and evapotranspiration. J. Environ. Qual., 14: 55-60. Tingey, D.T., Thutt, G.L., Gumpertz, M.L. and Hogsett, W.E., 1982. Plant water status influences ozone sensitivity of bean plants. Agric. Environ., 7: 243-254.
EVALUATION OF AN OZONE × MOISTURE
269
STRESS INTERACTION
M O D E L FOR S O Y B E A N
DAVID A. KING 1, ALLEN S. HEAGLE 2 and RICHARD B. FLAGLER 3
1 Department of Physical and Life Sciences, University of Portland, Portland, OR 97203 (U.S.A.) 2 U.S. Department of Agriculture, Agricultural Research Service, Plant Pathology Department, North Carolina State University, Raleigh, NC 27650 (U.S.A.) 3 Department of Crop Science, North Carolina State University, Raleigh, NC 27695-7630 (U.S.A.) (Accepted 22 September 1987)
ABSTRACT King, D.A., Heagle, A.S. and Flagler, R.B., 1988. Evaluation of an ozone × moisture stress interaction model for soybean. Ecol. Modelling, 41: 269-279. Assessments of air pollution impacts on crops may overestimate losses because they do not consider the impacts of soil moisture deficits on pollutant uptake by plants. A recent model of moisture stress × ozone interactions predicted reduced ozone (O3) impacts on yields of drought-stressed crops, due in part to an assumed reduction in the accumulation of 03 damage during drought. This paper describes an evaluation of the model with 03 × moisture stress field experiments on soybean conducted at Raleigh, NC, U.S.A. Modelled yield losses due to 03 were smaller than observed for moisture-stressed soybean, but these differences were not statistically significant. The model predictions were consistent with the 03 × H20 interaction observed by other researchers for soybean grown in a controlled environment.
INTRODUCTION O z o n e e x p o s u r e e x p e r i m e n t s have b e e n c o n d u c t e d o n a n u m b e r o f econ o m i c a l l y i m p o r t a n t c r o p s b y the N a t i o n a l C r o p L o s s A s s e s s m e n t N e t w o r k ( N C L A N ) to assess the effects o f o z o n e ( 0 3 ) o n the agricultural e c o n o m y o f the U.S.A. ( A d a m s et al., 1984). T h e s e assessments c o n c l u d e that a m b i e n t 0 3 levels s u b s t a n t i a l l y r e d u c e c r o p yields across large regions ( A d a m s et al.,
Reprint requests should be sent to: David King, Corvallis Environmental Research Laboratory, U.S. Environmental Protection Agency, 200 S.W. 35th Street, Corvallis, OR 97333, U.S.A. 0304-3800/88/$03.50
© 1988 Elsevier Science Publishers B.V.
270 1984; Heck et al., 1984). However, most of the field experiments used to estimate 03 effects have been conducted on adequately watered plants. Moisture stress caused by soil moisture deficits can reduce the occurrence of 03 injury symptoms by inducing stomatal closure (Dean and Davis, 1967; Tingey et al., 1982) and may also reduce 03 impacts on yield. Hence, assessments based on experiments with well-watered plants may overestimate losses caused by 03 . To evaluate the impact of soil moisture deficits on 03 damage to crops, N C L A N researchers have conducted moisture stress x 03 field exposure experiments, and constructed a crop simulation model to predict drought x O 3 interactions across geographic regions. The simulation model was applied to soybean, because this crop is sensitive to 03 and of great economic value (2nd to corn in the U.S.) (Adams et al., 1984). The model incorporates plant responses to moisture stress and 03 reported in the literature, but has not yet been tested against NCLAN experiments. This paper describes a test of the model using inputs from soybean moisture stress x 03 experiments conducted at Raleigh, NC. Because the object of interest is the potential shift in 03 effects on yield due to drought, the model was first calibrated for well-watered soybean and then run with water inputs from the water-stressed treatments. Comparison of modelled vs. observed water-stressed yields indicates the adequacy of the model. THE MODEL Plant uptake of CO 2 and 03, and loss of H20 through transpiration are all highly correlated because all three processes are mediated by the opening and closing of stomata. Transpiration plays a central role in the above processes because it influences soil water content which in turn affects stomatal behavior. Hence, transpiration was chosen as the central variable in modelling the 03 X moisture stress interaction. A complete description of the model is provided by King (1987). In the following section, we outline the general approach and specify those relationships involved in calibrating the model to the experimental data set. The model simulates soil moisture status and crop transpiration throughout the season, given daily inputs of rainfall and pan evaporation and hourly O 3 concentrations. Transpiration is calculated from pan evaporation for each day as modified by crop growth stage, cumulative 03 exposure, and soil water content of the previous day. Soil water content is then updated by balancing daily rainfall inputs against losses due to drainage and evapotranspiration. Soil water is assumed to limit transpiration when plant available water in the rooting zone falls below 1/2 of the potential available water at field capacity (Hanks, 1974; King, 1987).
271 The computation of 03 effects on transpiration is based on cumulative 03 exposure above a threshold level. For days of adequate soil moisture, the model computes an hourly 03 dose (Dh) as: D h = [03] - Zh, and D h = 0 ,
for for
[03] > T h
[03] < Th
(1)
where [03] is the mean 03 concentration over the hour in question and T h is an hourly mean threshold concentration which must be exceeded before any effects are expected. The daily dose (D i) is defined as the sum of the hourly dose over the daylight hours when stomata are likely to be open, i.e.
Di---EDh
(2)
03 exposure is assumed to cause a linear decline in transpiration as reported by Reich et al. (1985). This effect is modelled by computing a transpiration reduction factor:
Fi = E'-I "[- kOl
(3)
where F~_ 1 is the value of the factor on the previous day, and k is a constant denoting the sensitivity of transpiration to the 03 dose; F~ = 0 for the day of crop emergence and increases over the season with cumulative 03 exposure. The transpiration reduction factor is then used to calculate daily transpiration (T) for an O3-exposed crop relative to that of an unexposed crop (To) as: T / T o = 1 - F~
(4)
The mechanics of the model restrict F~ to values less than 1 so that the ratio T / T o lies between 0 and 1. Moisture stress impacts on the 03 effect are incorporated into the above calculation by decreasing the 03 dose of equations (1) and (2) on those days when soil moisture deficits limit transpiration (King, 1987). Specifically:
O h = ( T / T p ) TM [ 0 3 ] -
Th,
for
{(T/Tp) TM [O3]) > T h
and Dh=0,
for
{(T/Tp) TM [O31 } < rh
(5)
where Tp is the potential transpiration expected for a crop not impacted by soil moisture stress or 03 , and T is the transpiration predicted for a crop impacted by both of these stresses; values of T and Tp for the i - l t h day are used to compute the Dh's and D~ for the ith day, i.e., the model increments all variables based on their previous day's values and on the current day's water inputs, pan evaporation, and hourly 03 concentrations.
272 Thus, the modelled decrease in transpiration caused by O 3 damage increases as the season progresses, but the rate of accumulation of 03 effects is reduced during periods of soil moisture deficit. An additional interaction arises from the decrease in transpiration caused by 03 damage which results in less soil water depletion in O3-exposed crops. The estimated daily transpiration is summed over the growing season to define the total seasonal transpiration (ST). This estimate of ST is then multiplied by the transpiration efficiency (TE) to predict yield: TE denotes the yield per unit of water transpired. For this model, TE is assumed to be unaffected by moisture stress, but reduced by cumulative 03 exposure, as described by King (1987). By running the model for a range of O 3 and irrigation scenarios, one can predict how moisture stress should alter the yield response to 03 . METHODS
Experiments The field studies used to test the model were conducted at the U S D A - N o r t h Carolina State University Air Quality Field Research Laboratory, 9 km south of Raleigh, NC, U.S.A., in 1983 and 1984 (Flagler, 1986; Heagle et al., 1985, 1986, 1987). Open-top chambers (Heagle et al., 1973) were used to expose field-grown soybean to charcoal-filtered air (CF), nonfiltered air (NF), and N F air with different amounts of added 03 using methods described previously (Heagle et al., 1979). The experiments involved four 03 levels × two moisture treatments in 1983 and six 03 levels x two moisture treatments in 1984. Three and two replicates per 03 x moisture treatment were employed in 1983 and 1984, respectively. Details are summarized in Table 1. The soybeans were grown in a 28-cm deep layer of Norfolk loamy sand topsoil overlaying Appling sandy loam with approximately 20 cm of topsoil. Potential plant-available soil water (PSW) was only 1.9 cm for the Norfolk topsoil and about 2 cm for the Appling topsoil. Neutron probe estimates of soil moisture indicated only a small decline in soil moisture at 45-cm depth over the growing season. Hence, the rooting zone was taken to consist of only the above two layers and PSW was set at 4 cm for the model simulations. The two experimental moisture treatments, established by different irrigation frequencies, were well-watered (WW) and water-stressed (WS). The WW plots received 2.5 cm of water by drip tubing whenever soil water potential (~ks) dropped to - 0 . 0 3 MPa in any of the replicates of a given 03 treatment. The WS plots received 2.5-cm irrigations when leaf water potentials reached - 1 . 8 MPa (1983) or ~ks reached 0.5 MPa (1984) (Flagler,
273 TABLE 1 Description of soybean experiments used to test the model Cultivar: Davis Plant spacing: 19 plants per m of row (after thinning), 1.0 m between rows a Method of exposure: Constant additions of ozone to nonfiltered air from 9:00-16:00 EST, plus nonfiltered and carbon-filtered treatments Moisture stress: Two treatments, one maintaining adequate soil moisture, the other producing soil moisture deficits after mid-season (early August) Event
Planting Begin dispensing 03 First flower Begin pod fill End of flowering Physiological maturity Last day of 03 addition Final harvest
Date 1983
1984
16 June 7 July 10 August 4 September 13 September 15 October 24 October 9, 14 November
11 June 7 July 10 August 5 September 15 September 17 October 18 October 6 November
a Original stand 0.5 m, but thinned to 1.0 m row spacing by removing center row (5 plants at a time).
1986). Daily ~ks was monitored by one tensiometer per chamber, at a depth of 20 cm. Neutron probe estimates of ~Ps, taken at weekly intervals from a 22-cm depth, were used to schedule irrigations for the WS plots in 1984. Well-watered plots required a mean seasonal water supplement of 55 cm in 1983 and 26.3 cm in 1984; the 1983 growing season was hotter and drier than the 1984 season (Flagler, 1986). All WS plots received five irrigations on the same dates in both years, except for the two high-O 3 chambers of 1984, which received one less irrigation. One of the CF WS yields was discarded due to poor plant establishment for each year.
Model calibration The model was used to compute the yield of each chamber based on inputs of hourly 03 concentrations and daily water additions for each chamber. Daily pan evaporation values reported by the Weekly Weather and Crop Bulletin for Chapel Hill, NC (40 km NW of the experimental site) were used in the simulations. Potential plant available water (Psw) was increased with crop development in the model formulated by King (1987). Psw was fixed at 4 cm throughout the season in this study, because of the shallow rooting depth inferred for the Raleigh experimental site.
274 The model was originally calibrated to approximate the common soybean O3-response reported by Heck et al. (1983), when run with hourly 03 concentrations reported over daylight hours. However, the 03 impacts predicted for the WW treatments at Raleigh differed from the observed response, due in part to differences between experimental and ambient exposure conditions; the former included 7 - h / d a y 03 additions starting 3-4 weeks after planting. Since the main objective of the study was to test the ability of the model to predict impacts of drought on the crop response to 03, the model was recalibrated to mimic observed 03 effects for the WW treatments of each year. This calibration was accomplished by adjusting the 03 sensitivity parameter (k of equation 3) to minimize the variance between observed and modelled yields for the WW chambers. This parameter was set equal to 0.0165 1/~1 and 0.026 1/~1 for 1983 and 1984, respectively. Simultaneously, the damage threshold (Th of eqn. 1) was raised from the original value of 0.01 I~1/1 to 0.05 l~l/1, to improve the model fit to these WW yields. However, as Th is increased, the calculated ozone depression of transpiration decreases and modelled water use increases. To avoid this shift in water use, potential transpiration was reduced by 15% from that calculated by the original version of the model. Other model parameters were set at the values used by King (1987). The calibrated model was then used to simulate yield for each of the WS chambers. RESULTS Modelled and observed soybean yields are plotted as a function of 03 exposure in Figs. 1 and 2 for 1983 and 1984. Because the model was calibrated to predict the observed mean yield without water stress, a comparison of modelled vs. observed yields for the WS case indicates the accuracy of predicted drought impacts on yield. In both years, the model predicted smaller moisture stress impacts on mean WS yield than were observed, as shown in Table 2. This difference was significant ( P < 0.01) for 1983, but not for 1984. However, these difference were of modest size compared to total drought impacts. In 1983, water stress reduced observed mean yield by 51% while the model predicted a 37% effect. In 1984 the observed and modelled drought impacts were 20% and 16%, respectively. The model also predicted some moisture stress impacts on WW chamber yields, particularly for the charcoal-filtered treatment of 1984 where a 5% yield reduction by moisture stress was predicted. However, the magnitude of this prediction is uncertain because of possible errors in predicted evapotranspiration and the estimate of potential available soil moisture. The model predicted reduced sensitivity to 03 with moisture stress (Figs. 1 and 2), consistent with the model predictions presented by King (1987). The
275
500
400
j" 300 ED -J UJ
.............................
"(9".............
>ED
O
200
8
o
UJ UJ O9
8
oo
o I00
I
0
002
MEAN
I
I
I
t
004
006
008
0~0
0 ~2
7-H/DAY SEASONAL [03] (ppm)
Fig. 1. Soybean per-chamber, Raleigh, NC, 1983. Closed (e) and open ( o ) circles indicate well-watered (WW) and water-stressed (WS) treatments, respectively. The solid line denotes WW yields predicted by the model which was calibrated to fit the WW experimental data; the dotted line indicates the WS yields projected by the calibrated model. Seed yield was adjusted to a 13% water content and mean seasonal [03] was computed for 9:00-16:00 Eastern Standard Time over the exposure period.
nonlinear decline in WS yield predicted for 1984 was due in part to plants in the high-O 3 chambers receiving one less irrigation that year. The tendency for the observed values to fall below the modeled values for the higher WS 03 treatments of 1984 (Fig. 2) suggests a bias in the model prediction of the O 3 × H 2 0 interaction. However, an analysis of variance of the difference
500
% 400 ¢u •
¢m
300
O
O
6" ....................
ED _J uJ >E3
•
• 0 o
..... ~ - 3 •~
....... "'"...
o
o o
200
"GL •
UJ uJ 03 100
0
002
MEAN
0 0' 4
0 0'6
0.'10
0 0 '8
7-H/DAY SEASONAL
[03]
012
(ppm)
Fig. 2. Soybean yield per-chamber, Raleigh, NC, 1984. Symbols are defined in Fig. 1.
276 TABLE 2 Observed and modelled soybean yield per water stress treatment for well-watered (WW) and water-stressed (WS) treatments Treatment
Mean observed yield (g/m 2)
Mean modelled yield (g/m 2)
1983 WW 1983 WS 1984 WW 1984 WS
391.0 + 14.8 a 191.4 + 13.5 317.2+ 9.7 248.6 + 13.8
391.0 + 0.9 245.3 + 0.6 317.2+1.3 265.4 + 0.8
a + SE; standard errors were computed from mean square error per O3 × H20 treatment for the observed and modelled means. The difference between WW and WS yields was significar.tly greater for the observed than the modelled case for 1983 (P < 0.01).
TABLE 3 Analysis of variance mean squares for observed minus modelled yield of water-stressed soybean exposed to four levels of 03 in 1983 and six levels in 1984 Treatment
Source of variance
df
Mean squares of observed minus modelled yield
F value
Pr > F
1983 WS
03 Error 03 Error
3 7 5 5
2103 2008 1576 2086
1.05
0.5
0.76
0.5
1984 WS
The error was calculated from the within-O3-treatment variance of (observed-modelled yield). The error does not include model calibration error caused by experimental error in the well-watered yield values used to calibrate the model
b e t w e e n o b s e r v e d a n d m o d e l l e d W S yield i n d i c a t e d n o significant 0 3 effect o n this quantity, as s h o w n in T a b l e 3. T h e difference b e t w e e n o b s e r v e d a n d m o d e l l e d W S yield was negatively c o r r e l a t e d with 0 3 level, b u t n o t signific a n t l y so (r--- - 0 . 1 2 , 1983; r = - 0 . 3 8 , 1984). N o n e t h e l e s s , this t r e n d suggests that the m o d e l m i g h t u n d e r e s t i m a t e c r o p sensitivity to 0 3 in the presence of m o i s t u r e stress, i.e., the m o d e l overestimates the p r o t e c t a n t effect of m o i s t u r e stress. DISCUSSION O u r analysis did n o t reject the 0 3 × H 2 0 i n t e r a c t i o n p r e d i c t e d b y the m o d e l , b u t the test was weak, d u e to substantial e x p e r i m e n t a l variation. N o significant 0 3 × H 2 0 i n t e r a c t i o n was o b s e r v e d for either y e a r ( H e a g l e et al., 1985, 1986, 1987), so a m o d e l w h i c h p r e d i c t e d n o i n t e r a c t i o n w o u l d n o t h a v e
277 50
4O I-z
3o
J
.~ 2o Q
I0
l
o
o.os
I
oo9 [%] (ppm)
I
o.~s
Fig. 3. Aboveground biomass of 50-day old soybean plants exposed to constant 03 levels for 6.8-h/day, as reported by Amundson et al. (1986). The solid and dashed lines indicate well-watered and water-stressed treatments, respectively.
been rejected, either. The difficulty in testing the model has several sources. First, the impact of moisture stress on the O3-response is likely to be smaller than the O3-response itself. Second, including two moisture stress levels halves the number of chambers available to define the exposure response at a given water stress level. Third, any differences in soil moisture holding capacity between plots will increase yield variability with drought stress. Inclusion of higher 03 levels and more replicates would increase the power of experimental tests of the model. A significant O 3 × H 2 0 interaction was observed by A m u n d s o n et al. (1986) in pot-grown soybean. These researchers found that a moisture stress level which halved biomass production, substantially reduced the effect of 03, as illustrated in Fig. 3. Comparison of Figs. 1 and 3 indicates that A m u n d s o n et al.'s interaction was similar to that predicted by the model for severe drought. However, plant age and the indoor exposure system used by A m u n d s o n et al. differed substantially from field conditions. Further experiments are needed to determine if the 03 x H 2 0 interaction is different for field plants than for those in environmentally controlled chambers, before the above results can be taken as confirmation of the model. The model tested here focuses on soil moisture x O 3 interactions and does not consider atmospheric influences on the progression of 03 damage. The calibrated model sensitivity to 03 was 1.6 X greater for 1984 than 1983, suggesting that well-watered soybean was more sensitive to 03 in 1984. The regression slope of relative WS yield vs. [03] was also steeper for 1984 than 1983, although not significantly so. Soybean stomatal conductance and 03 uptake may be influenced by relative humidity a n d / o r vapor pressure deficit
278 (Vr'D), with less 0 3 uptake occurring at low humidity (McLaughlin and Taylor, 1981). This response would explain the above differences in sensitivity, as mean daily pan evaporation (July-September) was 30% greater for the 1983 experiment than for 1984, indicating higher VPD in the former year. California-grown cotton was also less sensitive to 0 3 during a year of high pan evaporation than for a year of low pan evaporation (Temple et al., 1985). Thus, our results do not preclude the possibility that atmospheric conditions may be as important as soil moisture in determining soybean sensitivity to ozone. ACKNOWLEDGEMENTS We thank Karen Randolph, James Reynolds, Luther Smith, and David Tingey for reviewing the manuscript and the National Crop Loss Assessment Network ( N C L A N ) Library for use of soybean chamber yield data. F u n d i n g for this project was provided by the U.S. Environmental Protection Agency under assistance agreement CR-812671 to the University of Portland. The project was administered by the EPA's Environmental Research Laboratory in Corvallis, OR. REFERENCES Adams, R.M., Hamilton, S.A. and McCarl, B.A., 1984. The economic effects of ozone on agriculture. EPA-600/3-84-090, U.S. Environmental Protection Agency, Corvallis, OR, 175 pp. Amundson, R.G., Raba, R.M., Schoettle, A.W. and Reich, P.B., 1986. Response of soybean to low concentrations of ozone: II. Effects on growth, biomass allocation, and flowering.J. Environ. Qual., 15: 161-167. Dean, C.E. and Davis, D.R., 1967. Ozone and soil moisture in relation to the occurrence of weather fleck on Florida cigar-wrapper tobacco in 1966. Plant Dis. Rep., 51: 72-75. Flagler, R.B., 1986. Effects of ozone and water deficit on growth, yield, and nitrogen metabolism of soybeans. Ph.D. dissertation, North Carolina State University, Raleigh, NC, 94 pp. Hanks, R.J., 1974. A model for predicting plant growth as influenced by evaporation and soil water. Agron. J., 66: 660-665. Heagle, A.S., Body, D.E. and Heck, W.W., 1973. An open-top field chamber to assess the impact of air pollution on plants. J. Eviron. Qual., 2: 365-368. Heagle, A.S., Philbeck, R.B., Rogers, H.H. and Letchworth, M.B., 1979. Dispensing and monitoring ozone in open-top fidd chambers for plant effects studies. Phytopathology,69: 15-20. Heagle, A.S., Flagler, R.B., Patterson, R.P., Lesser, V.M., Heck, W.W. and Mowry, F.L., 1985. Influence of soil moisture level on response of soybeans to 03. In: W.W. Heck, O.C. Taylor, R.M. Adams, J.E. Miller, E.M. Preston and L.H. Weinstein (Editors). National Crop Loss Assessment Network (NCLAN) 1983 Annual Report. EPA-600/3-85-061, U.S. Environmental Protection Agency, Corvallis, OR, 227 pp.
279 Heagle, A.S., Flagler, R.B., Heck, W.W., Cure, W.W., Lesser, V.M., Miller, J.E. and Corda, S.L., 1986. Influence of soil moisture on responses of soybean to O3. In: W.W. Heck, O.C. Taylor, R.M. Adams, J.E. Miller, D.T. Tingey and L.H. Weinstein (Editors). National Crop Loss Assessment Network (NCLAN) 1984 Annual Report. EPA-600/3-86-041, U.S. Environmental Protection Agency, Corvallis, OR, 228 pp. Heagle, A.S., Flagler, R.B., Patterson, R.P., Lesser, V.M., Shafer, S.R. and Hock, W.W., 1987. Injury and yield response of soybean to chronic doses of ozone and soil moisture deficit. Crop Sci., 27: 1016-1024. Heck, W.W., Adams, R.M., Cure, W.W., Heagle, A.S., Heggestad, H.E., Kohut, R.J., Kress, L.W., Rawlings, J.O. and Taylor, O.C., 1983. A reassessment of crop loss from ozone. Environ. Sci. Technol., 17: 572A-581A. Hock, W.W., Cure, W.W., Rawlings, J.O., Zaragoza, L.J., Heagle, A.S., Heggestad, H.E., Kohut, R.J., Kress, L.W. and Temple, P.J., 1984. Assessing impacts of ozone on agricultural crops: II. Crop yield functions and alternative exposure statistics. J. Air Pollut. Control Assoc., 34: 810-817. King, D.A., 1987. A model for predicting the influence of moisture stress on crop losses caused by ozone. Ecol. Modelling, 35: 29-44. McLaughlin, S.B. and Taylor, G.E., 1981. Relative humidity: important modifier of pollutant uptake by plants. Science, 211: 167-169. Reich, P.B., Schoettle, A.W. and Amundson, R.G., 1985. Effect of low level of 03, leaf age, and/or water stress of leaf diffusive conductance and water use efficiency in soybean. Physiol. Plant., 63: 58-64. Temple, P.J., Taylor, O.C. and Benoit, L.F., 1985. Cotton yield responses to ozone as mediated by soil moisture and evapotranspiration. J. Environ. Qual., 14: 55-60. Tingey, D.T., Thutt, G.L., Gumpertz, M.L. and Hogsett, W.E., 1982. Plant water status influences ozone sensitivity of bean plants. Agric. Environ., 7: 243-254.