•Here, we investigated the effects of increasing concentrations of ozone ([O3]) on soybean canopy-scale fluxes of heat and water vapor, as well as water use efficiency (WUE), at the Soybean Free Air Concentration Enrichment (SoyFACE) facility.
•Micrometeorological measurements were made to determine the net radiation (Rn), sensible heat flux (H), soil heat flux (G0) and latent heat flux (λET) of a commercial soybean (Glycine max) cultivar (Pioneer 93B15), exposed to a gradient of eight daytime average ozone concentrations ranging from approximately current (c. 40 ppb) to three times current (c. 120 ppb) levels.
•As [O3] increased, soybean canopy fluxes of λET decreased and H increased, whereas Rn and G0 were not altered significantly. Exposure to increased [O3] also resulted in warmer canopies, especially during the day. The lower λET decreased season total evapotranspiration (ET) by c. 26%. The [O3]-induced relative decline in ET was half that of the relative decline in seed yield, driving a 50% reduction in seasonal WUE.
•These results suggest that rising [O3] will alter the canopy energy fluxes that drive regional climate and hydrology, and have a negative impact on productivity and WUE, key ecosystem services.
The concentration of tropospheric ozone ([O3]) has approximately doubled since the start of the industrial revolution and is projected to continue to increase throughout the 21st century (Fowler, 2008). In addition to being a potent glasshouse gas, O3 is highly reactive and can impose damage to any sensitive biological surfaces with which it comes into contact. O3 is considered to be the most significant air pollutant with direct impacts on vegetation; damage for many species becomes apparent at concentrations well below the levels considered to be dangerous for human health (c. 40 parts per billion by volume (ppb; US EPA, 2006; Ainsworth et al., 2012). Concentrations above 40 ppb are commonly experienced by vegetation (Fowler et al., 1999; Morgan et al., 2006) and, as a result, there is clear evidence that O3 is already having a negative impact on the growth, physiology and yields of major food crops (Bergmann et al., 1999; Feng et al., 2003, 2010; Morgan et al., 2003; Timonen et al., 2004; Fiscus et al., 2005; Ainsworth, 2008; Betzelberger et al., 2010; Fishman et al., 2010). Yield losses present challenges to global food security, particularly as the global population increases beyond seven billion people. Meanwhile, O3-induced damage is predicted to already be decreasing the global value of crop production by $10 billion annually (Van Dingenen et al., 2009).
Crops dominate the area of arable land globally and contribute a significant fraction of terrestrial carbon exchange; therefore, the impact of elevated [O3] on crop biomass productivity can influence the global carbon cycle (Sitch et al., 2007; Ainsworth et al., 2012). The responses of crops to elevated [O3] extend beyond the assimilation of carbon into growth and yields. The energy available to an ecosystem is the net value of incoming and outgoing solar and terrestrial radiation (Sellers et al., 1997), and sensible and latent heat fluxes dominate the influence of vegetation on climate. As the stomata respond to the microenvironment surrounding the leaf, they are responsible for moderating the fluxes of matter and the partitioning of energy into and out of an ecosystem. Through the physiological control of stomata, plants have a large impact on climate; this is particularly true in continental interiors typical of most major crop producing areas (Sellers et al., 1997; Berry et al., 2010). Thus, the response of major crops to elevated [O3] can alter substantially the local, regional and global carbon and hydrologic cycles, and potentially provide a positive feedback on warming and/or drying of the planetary boundary layer.
The soybean–maize agro-ecosystem dominates the Midwestern US landscape and is the largest ecosystem in the contiguous USA. Therefore, O3-induced decreases in productivity and evapotranspiration (ET) of soybean could have an impact on the regional climate and hydrologic cycle in the Midwestern USA, particularly as this agriculturally productive area is located within a continental interior (e.g. Sellers et al., 1997). There are many physiological responses that occur when vegetation is grown in elevated [O3] that relate directly to the latent heat flux (λET). For example, growth in elevated [O3] can lower stomatal conductance (gs; Morgan et al., 2003), decrease biomass allocation to roots (Andersen, 2003) and slow the control of gs to changes in the leaf microenvironment (Wilkinson & Davies, 2010; Fiscus et al., 2012). Although stomatal responses are known to influence larger scale processes (Berry et al., 2010), evidence of elevated [O3] effects on λET for crops grown under open-air conditions is scarce. The previous chamber-based [O3] experiments do not maintain a natural microenvironment between the plant canopies and the atmosphere, or within plant canopies, which makes the interpretation of O3-induced effects on λET difficult (Elagoz & Manning, 2005). However, in previous experiments at the Soybean Free Air Concentration Enrichment (SoyFACE) facility, elevated [O3] (22–37% above background) resulted in soybean ET rates that were 11–13% lower for four of the five growing seasons, each with different climatic conditions (Bernacchi et al., 2011). It was hypothesized that the year with no O3-induced reduction in λET was an inherently low [O3] year, and concentrations, even with c. 30% increase in [O3] above background, did not impose sufficient damage to induce a response.
This study addresses the impacts on canopy fluxes for soybean grown under uniform climate and exposed to multiple [O3] in an exposure–response experiment. This experiment is the first to quantify canopy-scale responses of vegetation to multiple [O3] under open-air conditions, providing a unique opportunity to isolate the [O3] response of key fluxes with direct implications on regional-scale hydrology and climate. The first objective of this study was to determine the concentrations at which soybean λET is sensitive to O3, and whether decreases in λET are linked with the concentration of O3. If the amount of O3 exposure has an additive effect on decreasing λET, a negative correlation between O3 exposure and λET should be observed. Because λET and carbon gain are directly linked, the second objective of this study was to determine whether an increase in O3 has an impact on the amount of harvestable yield relative to the cumulative amount of water lost through ET over the growing season (harvestable water use efficiency (WUE); e.g. Hickman et al., 2010). In previous SoyFACE studies, it has been shown that the percentage decrease in seed yield (Morgan et al., 2006) is greater than the percentage decrease in growing season cumulative ET (Bernacchi et al., 2011); therefore, we predict that the harvestable WUE in our experiment will decrease with increasing [O3].
Materials and Methods
This research was conducted at the SoyFACE research facility located on the University of Illinois (USA) research farm (40.04 N, 88.24 W). The SoyFACE facility is situated in a 32-ha field in which soybean (Glycine max (L.) Merr.) and maize (Zea mays) each occupy half of the field and are rotated annually as is typical for Midwestern agriculture. Within this field, there are experimental plots that are 20 m in diameter.
For this experiment, FACE plots consisted of seven different soybean cultivars planted in 5.4-m long by eight-row-wide subplots. Row spacing was on 0.38-m centers. Micrometeorological sensors were placed on the side of the plot planted with G. max cv Pioneer 93B15 and situated so that the solar sensors were centered above each plot with the vertical mounting mast directly north to prevent shading. The cultivar chosen for this study is a cultivar commonly grown in commercial agriculture in the Midwestern USA and is the same cultivar as used for previous analyses of yield (Morgan et al., 2006) and ET (Bernacchi et al., 2011) at SoyFACE. Other information, including the agronomic practices employed at SoyFACE and a complete description of the field site, have been described previously (e.g. Bernacchi et al., 2005, 2006; Morgan et al., 2005).
Ozone concentrations were monitored continuously throughout the season using an O3 analyzer (model 49C O3 analyzer; Thermo Environmental Instruments, Franklin, MA, USA; Morgan et al., 2004) located in the center of the plot and directly adjacent to the cultivar used in this study. The central location of the 93B15 cultivar plots within the larger SoyFACE plots and the location at which [O3] was monitored were identical in all plots; this removed any influence of spatial gradients of ozone fumigation within the larger FACE plot. The O3 analyzers in all plots were calibrated yearly (calibration USA EPA Equivalent Method EQQA-0880-047, range 0 to 0.05–1.0 ppm; Morgan et al., 2006). The experimental design consists of eight individual plots each with different O3 set points (Table 1). The target [O3] for each plot was established before the initiation of the experiment, and the system was set to target these concentrations regardless of background [O3]. The fumigation system was based on Miglietta et al. (2001) and was on only during the day between 10:00 and 19:00 h central daylight savings time and only when the leaves were dry. These criteria resulted in seasonal increases lower than the set points (Table 1).
Table 1. Target and mean (± 1SE) achieved ozone concentration for each plot in the experiment
Target [O3] (ppb)
Mean [O3] achieved (ppb)
% 1-min mean [O3] within 20% of target
40 ± 0.9
46 ± 1.1
54 ± 1.6
58 ± 2.3
71 ± 3.2
88 ± 3.8
94 ± 5.0
116 ± 6.5
We used a residual energy balance approach to determine λET by calculating the latent heat flux (W m−2) using the sensible heat flux, soil heat flux and net radiation based on the equation:
Measurements were collected in 10-s intervals and averaged over 10-min periods throughout the growing season from planting until harvest using microloggers (CR1000 Microloggers, Campbell Scientific Inc., Logan, UT, USA). Net radiation was measured using single-channel net radiometers (Model Q*7; Radiation and Energy Balance Systems (REBS), Inc., Seattle, WA, USA) which were regularly repositioned to be 0.5 m above the crop canopy. A cross-calibration was performed before the growing season, as described previously (Bernacchi et al., 2007, 2011). Soil heat flux measurements were collected using one soil heat flux plate per plot (Model HFT-3, REBS, Inc.), buried at 10-cm depths at one-quarter spacing from the center row, and included the heat storage in soil above each heat flux plate, as described by Kimball et al. (1994).
The sensible heat flux was calculated as:
(ρa, density of air (kg m−3); cp, heat capacity of air (J kg−1 °C−1); Tc and Ta, canopy surface and air temperatures (°C), respectively; ra, aerodynamic resistance (s m−1)). The air temperature was measured using a thermistor (Model 107, Campbell Scientific, Inc.) mounted in a radiation shield (Model 41303-5A Radiation Shield, Campbell Scientific, Inc.) located in the center of the field. Surface temperatures were measured using infrared radiometers (IRR-P, Apogee Instruments, Inc., Logan, UT, USA) mounted on the north end of the plot facing south at a 25° angle from the vertical. Canopy surface temperatures in this case included both leaf and soil surface temperatures when the soil was exposed. The infrared radiometers were calibrated before each growing season as described previously (Triggs et al., 2004). Aerodynamic resistance was calculated on the basis of a previously described model (Jackson et al., 1987; Kimball et al., 1994, 1999; Triggs et al., 2004), which relies on wind speed (Model 12102D, R.M. Young Company, Traverse City, MI, USA), Ta, Tc, dew point temperature and canopy height. Canopy height was measured at regular intervals throughout the season and, on completion of the experiment, was fitted to a sigmoidal function. Additional meteorological measurements were collected as described previously (VanLoocke et al., 2010).
Seed yield was measured following complete senescence of soybean after the pods had matured and dried using typical agronomic practices. The harvested area in each plot was 11.2 m2. The middle six of the eight rows in the cultivar studied were used to measure seed yield. Of the 5.4 m of each row, the middle 4.9 m was carefully removed from the plots and the seeds were removed and weighed.
Micrometeorological data for each plot were collected at 10-min intervals throughout the growing season and analyzed using MATLAB (R2011b; The MathWorks, Inc., Natick, MA, USA). The mean daily [O3] values were based on averaging the measured [O3] for each plot over the 9-h period of fumigation described above. Cumulative O3 exposures above 40 ppb (AOT40) and ≥ 60 ppb (SUM06) were calculated based on the mean hourly [O3] during the entire 24-h period, as described previously (Mauzerall & Wang, 2001; Morgan et al., 2006). A regression analysis (SigmaPlot 12.2; Systat Software, Inc., San Jose, CA, USA) was used to test whether the slope of a dependent variable (e.g. canopy temperature, latent heat flux) differed statistically (P <0.05) from zero with changing [O3]. Independent variables (i.e. ET, H, G0, Tc and Rn) were averaged over the growing season to provide one mean value for each plot, with the exception of canopy temperature, in which both the midday mean (10:00–14:00 h) and daily mean were analyzed separately. Total ET (mm) was calculated by integrating the latent heat flux (W m−2) over the total period of measurement (day of year 191–269) and dividing by the latent heat of vaporization (λ; J kg−1). Harvestable WUE [(kg ha−1)/(mm)] is the ratio of the total harvested seed biomass (kg ha−1) to total ET (mm).
The 2009 growing season was characterized by relatively cool mean season temperatures (May to September mean of 19.6°C) compared with the 1970–2010 mean of 20.6°C based on the MRCC Applied Climate System (MACS) operated by the Midwestern Regional Climate Center, Illinois State Water Survey (http://mrcc.isws.illinois.edu/). Daily air temperatures, total solar radiation and vapor pressure deficits were variable throughout the growing season (Fig. 1). Precipitation over the growing season was 491 mm, compared with the 1970–2010 mean of 480 mm; however, the distribution was highly variable with a 23-d period late in the season in which only c. 5 mm of precipitation fell.
Despite daily variability, the fumigation resulted in a gradient in mean seasonal [O3] over the eight plots that ranged from 38 to 116 ppb (Table 1). The number of days in which O3 was applied to each plot varied on the basis of treatment. For example, the lowest [O3] treatment required less fumigation because background [O3] was frequently at or above the target concentration. However, the highest O3 treatment had a shorter growing season because of increased rates of senescence. Despite this variability, when the fumigation occurred, the quality of control was similar for all plots, except for the highest [O3] treatment where the 1-min averages were within 20% of the target only 67% of the time (Table 1). The cumulative values reflected in the AOT40 and SUM06 indices indicated an overall gradient in the treatment (Fig. 2). The reversal in AOT40 between the 160- and 200-ppb treatments (Fig. 2) resulted from over-fumigation in the 160-ppb plot and short-lived technical issues in the 200-ppb plot at the onset of this experiment.
Representative fluxes for a clear day (13 August 2009) for the lowest (40 ppb target [O3]) and highest (200 ppb target [O3]) plots showed distinct differences associated with Tc and the major fluxes (Fig. 3). Tc in the lowest and highest [O3] plots were relatively similar during the night; however, midday Tc values for the high [O3] plot were > 2°C warmer than for the lowest treatment. Differences in net radiation (Rn) were negligible at night and differences of < 20 W m−2 were observed during the day. The sensible heat flux (H) showed the largest difference during the day, with the highest [O3] plot having 40 W m−2 higher H relative to the lowest [O3] plot. No appreciable differences in soil heat flux (G0) were observed. Together, the three measured fluxes led to lower calculated latent heat flux (λET) in the highest relative to the lowest [O3] plot (Fig. 3).
Seasonal mean Tc increased linearly with [O3] (Fig. 4). A linear regression showed that, for each ppmh increase in AOT40, which, in this study, was nearly identical to a 1-ppb increase in seasonal mean [O3] (Fig. 4), seasonal mean Tc increased by 0.015°C and midday increases were double those determined using the whole day (Fig. 4). The regressions for Tc calculated using the 24-h data (F1,6 = 18.42, P =0.005) and using the midday values (F1,6 = 27.42, P =0.002) were statistically different from zero. Seasonal mean H also increased linearly with rising [O3], with a slope that differed significantly from zero (F1,6 = 23.22, P =0.003). Neither G0 nor Rn showed any observable relationship with [O3] (Fig. 4). However, because of the inherent variability associated with an upward-facing sensor, there was relatively large variability over the growing season of c. 25 W m−2 for average Rn from the lowest to the highest mean value. Because of the variability associated with Rn, and the importance of this variability on the estimation of season-long ET, the [O3] plot in which Rn most closely represented the mean Rn for all plots (plot 8, mean [O3] of 58 ppb) was used for further analysis.
Visualization of the variables that were sensitive to [O3] over the diurnal time course showed that the gradients in H, λET and Tc were dominant over the daylight period and little or no differences were observable at night (Fig. 5). The ratio of H to λET, defined as the Bowen ratio (β), showed a significant repartitioning of upward energy fluxes away from λET and towards H during the day (Fig. 5). Because H and λET approach zero during the evening, β is susceptible to large oscillations from large positive to large negative; therefore, the scale presented is limited to from −2.0 to 0.5 to emphasize the ratio when fluxes were relatively large.
Total ET declined linearly with [O3] (F1,6 = 18.6, P =0.005) with the highest [O3] treatment using c. 26% less water than the lowest [O3] treatment (Fig. 6). Harvested seed yield declined sharply (F1,6 = 371.9, P <0.0001) showing c. 64% reduction in yields in the highest relative to the lowest [O3] treatment (Fig. 6). Thus, WUE decreased linearly (F1,6 = 124.9, P <0.0001) with [O3] being c. 50% lower in the highest relative to the lowest [O3] plot.
This study demonstrates that, as [O3] rises, soybean canopy ET and yield decrease linearly, whereas the sensible heat flux and canopy temperature increase linearly. These results build on a previous experiment in which soybean was grown in elevated [O3] over five different growing seasons (Bernacchi et al., 2011). The previous experiment increased [O3] to a set point that ranged across all growing seasons from 22 to 37% above the variable background ozone concentrations, with season means ranging from 46 to 68 ppb (Bernacchi et al., 2011). In the previous study, in four of five seasons, the moderate increase in [O3] decreased canopy ET. In the current study, eight plots of soybean were each grown under different concentrations of [O3] within one growing season, with as little variability as possible in the concentrations within and between days. Thus, here, we were able to isolate the consequences of rising [O3] from the variation in climatic variables, variation in planting date, day-to-day variation in [O3] and crop management.
The regression analysis for ET indicates that, for each ppmh increase in AOT40, or approximately each ppb increase in season mean [O3], season integrated ET decreases by 1 mm. The [O3] response observed in the current study is very similar to that observed previously when compared against the AOT40 index; however, this study shows considerably less variability (r2 = 0.76) relative to the previous study (r2 = 0.23; Fig. 6). Because the current study focuses on soybean grown under different [O3] with identical management and climatic conditions, the climate-induced variability is not confounded by treatment responses as in previous studies. It also suggests that the seasonal variability in [O3] drives significant changes in ET and, perhaps, in local and regional hydrologic cycles.
The decrease in ET with rising [O3] probably results in increased soil moisture, which has been observed previously to maintain ET in FACE experiments (Bernacchi et al., 2007, 2011). Soil moisture was not measured for this experiment; however, there was no observable evidence that ET was maintained by increased soil moisture in the higher [O3] plots. This may be a result of decreases in root growth with elevated [O3] (e.g. Blum & Tingey, 1977; Andersen, 2003), limiting the ability of soybean to take up soil water regardless of the moisture availability. Another explanation is that accelerated senescence (Morgan et al., 2006) in the highest [O3] may have negated the effect of greater soil moisture on ET.
The decline in ET associated with increasing [O3] was accompanied by an increase in canopy temperatures (Fig. 4). The difference in Tc was dominated by daytime temperatures (Fig. 5); however, although relatively small, there were observed increases in soil temperature during the night (data not shown). This increase in night temperatures is consistent with previous results (Bernacchi et al., 2011) and is probably driven by increased solar radiation absorption by soil because of the lower total above-ground biomass, providing less shading. Although the effect of higher Tc at night has little or no impact on λET, there are potential impacts, as with higher daytime temperatures, on ecosystem function related to soil respiration, as well as feedbacks between vegetation and regional climate.
Ozone is already causing reduced yields in many crop species (Bergmann et al., 1999; Feng et al., 2003, 2010; Morgan et al., 2003; Timonen et al., 2004; Fiscus et al., 2005; Karlsson et al., 2005; Wang et al., 2007; Ainsworth, 2008; Betzelberger et al., 2010; Fishman et al., 2010; Ainsworth et al., 2012), but it is difficult to determine how much current rates of ET might be influenced by current tropospheric [O3]. Our analysis indicates that increasing [O3] beyond 40 ppb will cause a linear decrease in ET, and the decrease in soybean seed yield is accelerated relative to ET. As a result, an almost 50% reduction in WUE was observed from the lowest to the highest treatment. Because the losses in seed yield exceeded the decrease in ET, there are consequences to the ecosystem services beyond lost productivity, including reductions in WUE. The results also support the selection of soybean cultivars with high WUE not just as an adaptation to drought, but perhaps as an adaptation to rising [O3]. Whether the same observations would be made if WUE was calculated using whole-plant or total above-ground biomass is uncertain. However, previous studies on soybean biomass productivity and yields for soybean grown in elevated [O3] at SoyFACE (Morgan et al., 2006) have shown no impact of [O3] on harvest index. Therefore, assuming that the total above-ground biomass responses are similar to the measured yield responses, it is likely that a metric using above-ground biomass would be similar.
The maize–soybean agro-ecosystem dominates the land use in the Midwestern USA and represents the largest continuous ecosystem type in the temperate USA. The impact of atmospheric change on the Bowen ratio for soybean is likely to have an impact on regional climate and hydrology given the size and location of this ecosystem (e.g. Sellers et al., 1997). Consistent with previous experiments (Bernacchi et al., 2011), these results suggest that future increases in [O3] will decrease ET for soybean. Further implications of these results include changes in local and regional meteorological conditions through warmer surface temperatures and perturbations to the hydrologic cycle via decreased water vapor release to the atmosphere in which soybean, and perhaps other major crops, are grown (e.g. Georgescu et al., 2011). Although the implications for hydrology and climate conditions are speculative, the results presented here provide the foundation in which these effects can be investigated through coupled land-use/ecosystem models to provide a more defensible estimate of the large-scale impacts of increasing [O3].
The authors would like to acknowledge Don Ort in managing the SoyFACE facility, Tim Mies and Charlie Mitsdarfer in maintaining the ozone treatment, Benjamin Castellani and Pat Schmitz in assisting with technical aspects of the micrometerological measurements and Randy Nelson in assisting with planting and harvesting. We would also like to thank the three anonymous referees for their helpful comments. This work was supported in part by the Agriculture and Food Research Initiative competitive grant no. 2010-65114-20355 from the USDA National Institute of Food and Agriculture to E.A.A., as well as the USDA-ARS.