Benefits of increasing transpiration efficiency in wheat under elevated CO2 for rainfed regions
AbstractHigher transpiration efficiency (TE) has been proposed as a mechanism to increase crop yields in dry environments where water availability usually limits yield. The application of a coupled radiation and TE simulation model shows wheat yield advantage of a high-TE cultivar (cv. Drysdale) over its almost identical low-TE parent line (Hartog), from about −7 to 558 kg/ha (mean 187 kg/ha) over the rainfed cropping region in Australia (221–1,351 mm annual rainfall), under the present-day climate. The smallest absolute yield response occurred in the more extreme drier and wetter areas of the wheat belt. However, under elevated CO2 conditions, the response of Drysdale was much greater overall, ranging from 51 to 886 kg/ha (mean 284 kg/ha) with the greatest response in the higher rainfall areas. Changes in simulated TE under elevated CO2 conditions are seen across Australia with notable increased areas of higher TE under a drier climate in Western Australia, Queensland and parts of New South Wales and Victoria. This improved efficiency is subtly deceptive, with highest yields not necessarily directly correlated with highest TE. Nevertheless, the advantage of Drysdale over Hartog is clear with the benefit of the trait advantage attributed to TE ranging from 102% to 118% (mean 109%). The potential annual cost-benefits of this increased genetic TE trait across the wheat growing areas of Australia (5 year average of area planted to wheat) totaled AUD 631 MIL (5-year average wheat price of AUD/260 t) with an average of 187 kg/ha under the present climate. The benefit to an individual farmer will depend on location but elevated CO2 raises this nation-wide benefit to AUD 796 MIL in a 2°C warmer climate, slightly lower (AUD 715 MIL) if rainfall is also reduced by 20%.
1 INTRODUCTIONHigher transpiration efficiency (TE) has been proposed as a mechanism to increase crop yields in dry environments where reduced water supply limits biomass and yield (Craufurd, Austin, Acevedo, & Hall, 1991; Ehdaie, Hall, Farquhar, Nguyen, & Waines, 1991; Martin & Thorstenson, 1988; Passioura, 1977). Crop level TE can be defined as the ratio of biomass gain over transpiration, and is related to leaf-level TE and approximations of TE that include soil evaporation (e.g., evapotranspiration or total water use, also termed water use efficiency). The nature of TE, comprising components of biomass and transpiration, contributes to it being a complex trait from a breeding point of view (Richards & Condon, 1993). This complexity is increased because of TE’s dependence on environmental factors like vapor pressure deficit (VPD) of the atmosphere, whereby TE is reduced as VPD increases (Tanner & Sinclair, 1983). As such, it is difficult to separate the genetic components of TE from the environmental components, but as Sinclair (2012) showed, it is possible to do this by defining TE as an inverse function of VPD (TE = kd/VPD). The resulting crop-dependent transpiration coefficient (kd) offers a way to normalize TE against changing VPD. Under typical dryland field conditions, TE for wheat varies from around 3 to 9 g of biomass growth per kg water transpired with kd typically ranging from 4 to 6 Pa (Kemanian, Stöckle, & Huggins, 2005). Older cultivars appear to have a lower potential (“unstressed”) TE (i.e., when measured under ample water supply and low VPD) than more recently released cultivars, and that has been attributed to rising atmospheric CO2 concentrations over recent years (Fletcher & Chenu, 2015). Crop TE itself can vary more than the assumed constant kd, particularly when water stressed under high VPD or under increasing atmospheric CO2. However, varied assumptions of total biomass accumulation (i.e., shoot + root or shoot only) and consistent VPD algorithms for the sampling period contribute to the observed variance for which more complex models of TE apply (Kemanian et al., 2005). The stable isotope (δ13C) signature in biomass has been used as a surrogate for leaf-level TE, to produce high-TE wheat cultivars (Condon, Richards, Rebetzke, & Farquhar, 2004; Rebetzke, Condon, Richards, & Farquhar, 2002). This was based on the original work relating carbon isotope discrimination (CID) to TE in wheat (Farquhar & Richards, 1984). This original work also delineated the important distinction between carbon isotope composition, δ13C, and the biologically meaningful process of CID. Field evaluation of the high-TE cultivar (Quarrion) showed significant gains in TE (11%–21%) over a season measured against a low-TE cultivar (cv. Matong) but realizing final yield was more complex than just biomass gain (Condon & Richards, 1993). The complexity comes from disproportionate changes in transpiration and biomass, with changes in assimilate partitioning considered independent of those factors that primarily control TE (e.g., VPD). This partitioning is particularly important when considering grain yield, because grain growth occurs later in the season when crops are typically water-limited and experiencing terminal drought and crops have the capacity to shift varying amounts of C assimilated earlier in the season into the grain. This early work showed significant advantage of related high-TE lines over low-TE lines in drier locations (e.g., Rebetzke et al., 2002) but the benefits over a wider range of environmental conditions remain largely unknown. An independent assessment of the value of TE was undertaken separately by Australian Grains Technology® breeding company. They grew a high-TE cultivar, Drysdale, side-by-side with its closely related low-TE parent Hartog across 60 site-year combinations throughout the Australian wheat belt (Rebetzke et al., 2009). Their studies confirmed the significant yield benefit of greater TE across a broader range of environments ranging in yield from 0.3 to 6 t/ha, and a particular benefit of high TE at yields of 4 t/ha and below. Among changing environmental factors, increasing atmospheric CO2 will increase leaf-level TE for virtually all plants because elevated CO2 promotes C assimilation and at the same time decreases stomatal conductance and therefore transpiration. Recent work from the Australian Grains Free-Air Carbon Dioxide Enrichment (AGFACE) facility provided some evidence that a high-TE trait might still be an advantage under higher atmospheric CO2 concentrations (Tausz-Posch, Norton, Seneweera, Fitzgerald, & Tausz, 2013; Tausz-Posch, Seneweera, Norton, Fitzgerald, & Tausz, 2012). High-TE cultivar Drysdale was grown side-by-side with low-TE parent Hartog and while both cultivars in this analysis had improved TE under elevated CO2, differences between the two cultivars indicated greater TE for Drysdale with growth under elevated CO2 potentially increasing the response of this trait. The exact mechanisms for this increasing advantage were not entirely clear (Tausz-Posch et al., 2012). Additionally, the AGFACE experiment does not fully represent a future climate even at its present location in Horsham, Australia. We therefore used crop simulation modeling to (1) better understand the genetic and environmental components of TE in these experiments, and (2) extrapolate experimental observations to other environments beyond this site. Specifically, we explored potential benefits of increased TE in wheat across the wheat growing areas of Australia employing a validated model considered sufficiently mechanistic to model water-limited wheat crop growth and yield. We consider these effects under the present climate and likely future warmer and drier climate scenarios under elevated atmospheric CO2 concentrations. This study region represents a large proportion of global wheat production areas and is typical of many rainfed cropping environments throughout the world experiencing significant changes in climate (e.g., CIMMYT Mega environment 1, 2, 4, and 8; CIMMYT 2014).
2 MATERIALS AND METHODSWe reanalyzed the published data from Tausz-Posch et al. (2012) using the CAT-wheat model (O’Leary et al., 2015). The model (CAT-Wheat) is a landscape-scale model that has recently been successfully tested against other AGFACE data (O’Leary et al., 2015). The advantage of the CAT model is its unique feature of analyzing crop performance across diverse landscapes (Christy et al., 2013).
2.1 Experimental site and growing conditionsA detailed description of the site set-up is given in Mollah, Norton, and Huzzey(2009). Briefly, the Australian Grains Free Air CO2 Enrichment (AGFACE) facility is located at Horsham, Victoria, Australia (36°45′07″S, 142°06′52″E, 127 m above mean sea level). The site is a clay vertosol (Isbell, 1996), which has ~35% clay at the soil surface increasing to 60% at 1.4 m depth. Four ambient CO2 (a[CO2], 375 mol/mol) and four elevated CO2 (e[CO2], 550 mol/mol) plots (each 12–16 m in diameter) were used. Plots are randomly allocated within each ring. In 2009, one experimental series was sown within the time frame of standard local practice (23 June 2009; Table 1) and a second experimental series was sown later (19 August 2009; Table 1) in order to create a set of drier and hotter growing conditions. In 2010, a third experimental series was run, sown within the time frame of standard local practice (sowing date 27 May 2010; Table 1). In addition, each of the three experimental series was run under rainfed conditions and supplemental irrigation. This resulted in three additional sets of environmental growing conditions (Table 1). Closely related cultivars “Drysdale” and “Hartog” were sown into flat beds at 0.27 m row spacing on the plots. The high-TE Drysdale was selected from a backcross-2 population (Hartog × 3/Quarrion) using Hartog as the low-TE recurrent parent. Summarizing, a total of six different environments were tested under both ambient CO2 (375 mol/mol) and elevated CO2 (550 mol/mol) concentrations, using differing combinations of water supply, seasonal, and sowing date variations (Table 1). Summary of data underlying the results reported in Tausz-Posch et al. (
|Time of sowing||Rain (mm)||Irrigation (mm)||Measurement||Hartog||Drysdale|
|23/06/09||223||0||Biomass DC65 (g/m2)||821.7||1,104.9||764.4||952.6|
|Biomass DC90 (g/m2)||843.6||876.8||870.9||1,109.6|
|Grain yield (g/m2)||221.3||200.2||252.2||277.8|
|23/06/09||223||70||Biomass DC65 (g/m2)||817.2||836.4||889.8||998.0|
|Biomass DC90 (g/m2)||923.0||984.2||1,046.2||1,035.2|
|Grain yield (g/m2)||246.2||219.6||287.6||270.2|
|19/08/09||187||0||Biomass DC65 (g/m2)||453.1||507.7||358.0||496.7|
|Biomass DC90 (g/m2)||505.8||535.7||444.4||686.2|
|Grain yield (g/m2)||136.1||136.7||122||163.0|
|19/08/09||187||60||Biomass DC65 (g/m2)||473.4||585.4||422.4||621|
|Biomass DC90 (g/m2)||497.9||686.6||485.2||757.3|
|Grain yield (g/m2)||125.1||172.6||122.9||228.2|
|27/05/10||296||0||Biomass DC65 (g/m2)||937||1,114.1||1,000.1||1,224.2|
|Biomass DC90 (g/m2)||1,546.1||1,712.8||1,429.4||1,714.4|
|Grain yield (g/m2)||467.7||576.6||500.5||598.8|
|27/05/10||296||80||Biomass DC65 (g/m2)||939.3||1,114.2||943.6||1,209.4|
|Biomass DC90 (g/m2)||1,666.1||1,939.9||1,624.4||2,067.3|
|Grain yield (g/m2)||591.9||631.5||537.6||776.0|
2.2 Biomass, grain yield, and morphological measurementsFor each experimental series, total above-ground biomass (leaves, stems, spikes) was measured at flowering (growth stage DC65; Zadoks, Chang, & Konzak, 1974) and at physiological maturity (DC90). As phenological development was similar for both cultivars and in both CO2 treatments, both cultivars grown under ambient and elevated CO2 were sampled on the same dates. At each sampling date, plants from 0.5 m2 of each subplot (“whole sample”) were hand-harvested and then dried for 72 hr at 70°C (DC65) or 40°C for 72 hr (DC90). The DC65 samples were weighed while DC90 samples processed for grain yield, above-ground biomass and 1,000 kernel weight. All parameters were expressed on an area basis (m2).
2.3 The CAT-Wheat modelThe CAT-Wheat model originally calculated crop growth by a radiation use efficiency (RUE) approach whereby reduced water supply, nutrient stress or photoperiod factors reduced RUE by relative differences (O’Leary et al., 2015). The minimum value of these factors (i.e., the most limiting) was used to reduce RUE. While that version of the model performed satisfactorily in testing the response to elevated CO2, it did not simulate transpiration reduction directly as a consequence of high CO2. The model was modified here to increase its utility in simulating water dynamics similar to other contemporary models. Initial parameter adjustments were made using the OLEARY-CONNOR model (O’Leary & Connor, 1996) utilizing parameters driven by TE for determining growth, and software coding modifications to establish realistic amendments that were subsequently transferred to the landscape CAT-Wheat model. These two models are not identical and differ in assimilate partitioning and water and nitrogen simulation calculations. Transpiration reduction and efficiency changes due to elevated CO2 were added to CAT based on a formulation adapted from Stöckle, Williams, Rosenberg, and Jones (1992) as incorporated into the CROPSYST (Stöckle, Donatelli, & Nelson, 2003) and STICS (Brisson et al., 2003) models. A correction to RUE is applied and the associated correction to TE, without double accounting, was made after O’Leary et al. (2015). The fertilization effect of elevated CO2 is achieved by multiplication of TE by a factor (TECC) that is derived from a RUE factor (RUECC) from Stöckle et al. (1992) with simplifying assumptions of aerodynamic resistance of crop canopy 300 s/m and canopy resistance of 36 s/m at 350 μmol/mol CO2 (O’Leary et al., 2015);
(2)where, CO2 is the atmospheric CO2 concentration (μmol/mol) and γ (kPa/°C) and δ (kPa/°C) are the psychometric constant and slope of saturated vapor pressure–temperature curve, respectively such that RUECC = 1, 1.18 and 1.23 at 350, 550, and 650 μmol/mol, respectively. We calculated γ and δ as follows:
(4)where, T is the daily mean air temperature (◦C) and El is the height above sea level (m) (Allen, Pereira, Raes, & Smith, 1998). Potential crop transpiration is reduced by elevated CO2 in proportion to the ratio of RUECC/TECC that provides a TECC of 1.27 at 650 μmol/mol CO2. At very high levels of CO2, RUECC asymptotically approaches 1.7.
2.4 The CAT-Wheat model ̶ Crop parameterizationThis modified CAT-Wheat model was parameterized against the field data of cultivars Drysdale (high TE) and Hartog (low TE, near isogenic to Drysdale), ensuring observed phenological stages of DC65 and DC90 were matched. To reflect the similar genetic background, both Hartog and Drysdale were parameterized identically with the exception of two parameters, viz; crop transpiration coefficient and crop canopy resistance (Table 2). For each time of sowing, the model was initialized to match measured sowing soil water content and available mineral N content through the soil profile (pooled across the experiment). Irrigation and fertilizer were applied by the model on the actual days of application. Key parameters used to define wheat growth in CAT-Wheat for cultivar Hartog and Drysdale
|Base temperature for vernalization||2||2||°C|
|Max temperature for vernalization||9||9||°C|
|Vernalization days required||24||24||day|
|Threshold temperature for thermal requirement: sowing to emergence||4||4||°C|
|Threshold temperature for thermal requirement: sowing to stem elongation||4||4||°C|
|Threshold temperature for thermal requirement: sowing to anthesis||4||4||°C|
|Threshold temperature for thermal requirement: anthesis to maturity||8||8||°C|
|Thermal time between sowing and crop emergence||78||78||°C day|
|Thermal time between sowing and stem elongation||430||430||°C day|
|Photothermal time between sowing and anthesis||340||340||hr °C day|
|Thermal time between anthesis and maturity||550||550||°C day|
|Maximum photosynthetic (leaf + stem) area index||5||5||m2/m2|
|Proportion of Max PAI (1st point)||0.05||0.05||0 to 1 scalar|
|Proportion of growing season (1st point)||0.20||0.20||0 to 1 scalar|
|Proportion of Max PAI (2nd point)||0.95||0.95||0 to 1 scalar|
|Proportion of growing season (2nd point)||0.50||0.50||0 to 1 scalar|
|Crop transpiration coefficient||5.2||6.0||Pa|
|Crop canopy resistance||36||44||s/m|
|Maximum grain growth rate||2||2||mg/day|
|Maximum grain size||50||50||mg|
|Grain number coefficient (intercept)||2,000||2,000||grains/m2|
|Grain number coefficient (slope)||10.51||10.51||grains/g|
|Maximum proportion of biomass at anthesis that can be translocated to grain||20||20||%|
(6)where, rs is the crop canopy resistance (s/m).
2.5 The CAT-Wheat model ̶ Long-term analysis at HorshamThe CAT-Wheat model was applied to consider the productivity change resulting from increasing TE in wheat at the FACE experimental site using daily climate data from 1962 to 2015 resulting in 54 crop years of modeled data. Daily climate data for the Horsham (Horsham Polkemmet Rd, Station number 79023 (36°39′41″S, 142°04′07″E)) climate station (located 10 km from the site) were sourced from the Australian Bureau of Meteorology (www.longpaddock.qld.gov.au/silo, accessed 25 January 2018). The long-term modeling conducted considered both Hartog and Drysdale at ambient (375 μmol/mol) and elevated (550 μmol/mol) CO2 concentrations for the whole historic 54 year sequence (Historic climate), plus two additional climate sequences: the first additional sequence was created by increasing the daily average temperature by 2°C over the 54-year period (Historic climate 2°C warmer), while the second sequence increased the daily average temperature by 2°C and decreased daily rainfall by 20% (Historic climate 2°C warmer and 20% less rainfall). These changes were selected to approximate a warmer and drier climate expected by 2050 in this region to indicate expected sensitivity of the crop traits. The CAT-Wheat model was applied for the two wheat cultivars sown each year after the “autumn-break” (defined as at least 20 mm rainfall in a 5-day period between 14 April and 30 June). In summary, 12 separate 54 year simulations were conducted that comprised two cultivars by three climates by two CO2 concentrations totaling 648 years of simulations. To reduce the confounding effect of “carry-over” stored soil water from the previous year’s crop, the stored soil water status was reset 75 days before sowing to 10% plant available water for each soil depth increment to a total depth of 1 m, and a full plant available water profile below that depth.
2.6 The CAT-Wheat model ̶ Spatial analysis across AustraliaThe long-term analysis at Horsham was extended across Australia over a 54-year period using historic climate and the two additional climate sequences using the same method applied for the long-term analysis at Horsham. Model simulation was conducted on all privately owned, arable agricultural land (defined as slopes <5%) within the spatial region identified in Figure 1. The spatial area was divided into 1-km2 grid cells for modeling. For each grid cell within this region, the CAT-Wheat model was applied for the two wheat cultivars sown each year after the “autumn-break,” with crop yield response demonstrating intraseasonal variability associated with climate patterns and soil water availability.
3.1 Model performance against experimental data at the AGFACE siteWe were able to reproduce an accurate simulation against the observed biomass at anthesis and maturity and grain yield for both Drysdale and Hartog across the various irrigation and CO2 treatments (Figure 2). The slope of the simulated vs. observed response was near unity (range of 0.93–1.03) with a calculated root mean square error (RMSE) of 94, 91, and 74 (g/m2) for biomass at anthesis and maturity, and grain yield, respectively. Similarly, across our larger dataset the model is seen to be unbiased (slope of 0.998 and 0.982) with similar accuracy with a RMSE 71 g/m2 (Figure 2d). The cumulative simulated transpiration by Drysdale to anthesis for the 12 crops was 17 mm (1.4%) lower than Hartog, resulting in an additional 60 mm (5.1%) plant available water being available for Drysdale for grain filling. The slope values in Figure 3 are a representation of the growth response (observed and modeled) of a number of variables to elevated CO2 as by default, this slope value reports the response to elevated CO2 by dividing the elevated measurement (e.g., grain yield) by the ambient measurement. Based on these slope values, the model simulated (within 3%) the large differential yield response between Drysdale and Hartog to elevated CO2 which is consistent with the empirical data reported by Tausz-Posch et al. (2012; Figure 3) by using two cultivar-parameters (Table 2), the TE coefficient and crop canopy resistance. The exception was the grain yield CO2 response for Drysdale (Figure 6f) with its observed slope of grain response to elevated CO2 being 27.5% above unity compared to the modeled 18.3%.
3.2 Long-term responses at HorshamWe applied the simulated trait differences between Drysdale and Hartog over 54 years of present and future climate scenarios at Horsham (Figure 4). As sowing data were based on an amount of rainfall falling at an “autumn-break,” there was no impact on the average sowing date by raising temperature by 2°C. However, the third climate sequence of reduced rainfall delayed the average sowing date by 16 days (Table 3). The increase in temperature did decrease the length of growing season which resulted in reduced growing season rainfall for the two climate sequences which were elevated by 2°C (Table 3).
|Average sowing date||Average physiological maturity date||Average growing season rainfall||Average growing season temperature|
|Historic climate 2°C warmer||17-May||26-Nov||300||13.6|
|Historic climate 2°C warmer and 20% less rainfall||2-Jun||30-Nov||226||13.8|
3.3 Responses across Australian arable landThe application of the model across all arable land between 221 and 1,351 mm annual rainfall under the present-day climate showed a mean yield advantage of Drysdale over Hartog from about −7 to 558 kg/ha (mean 187 kg/ha) (Figure 5a). However, there was large spatial variance, with the smallest response in the drier areas of Western Australia, South Australia New South Wales and Queensland, along with the higher rainfall regions of Western Australia, South Australia and Victoria. Under elevated CO2 conditions, the response of Drysdale was much greater overall, ranging from 51 to 866 kg/ha (mean 284 kg/ha), with the greatest response tending toward the wetter areas (Figures 1 and 5b). Under warmer, drier climates (Figure 5e,f) yield advantage of Drysdale declined more in the higher rainfall regions of the study area.
|Climate||CO2 (mol/mol)||Mean yield difference (kg/ha)||AUD ($MIL) difference attributed to transpiration efficiency genetic coefficient|
|Current + 2°C||375||152||513|
|Current + 2°C||550||236||796|
|Current + 2°C −20% rainfall||375||143||482|
|Current + 2°C −20% rainfall||550||212||715|