Glenn Fitzgerald

Benefits of increasing transpiration efficiency in wheat under elevated CO2 for rainfed regions

Higher 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 558xa0kg/ha (mean 187xa0kg/ha) over the rainfed cropping region in Australia (221-1,351xa0mm 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 886xa0kg/ha (mean 284xa0kg/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 (5xa0year average of area planted to wheat) totaled AUD 631 MIL (5-year average wheat price of AUD/260xa0t) with an average of 187xa0kg/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%.

Virus incidence in wheat increases under elevated CO2: A 4-year study of yellow dwarf viruses from a free air carbon dioxide facility

The complexities behind the mechanisms associated with virus-host-vector interactions of vector-transmitted viruses, and their consequences for disease development need to be understood to reduce virus spread and disease severity. Climate has a substantial effect on viruses, vectors, host plants and their interactions. Increased atmospheric carbon dioxide (CO2) is predicted to impact the interactions between them. This study, conducted under ambient and elevated CO2 (550μmolmol-1), in the Australian Grains Free Air Carbon Enrichment facility reports on natural yellow dwarf virus incidence on wheat (including Barley/Cereal yellow dwarf viruses (B/CYDV)). A range of wheat cultivars was tested using tissue blot immunoassay to determine the incidence of four yellow dwarf virus species from 2013 to 2016. In 2013, 2014 and 2016, virus incidence was high, reaching upwards of 50%, while in 2015 it was relatively low, with a maximum incidence of 3%. Across all years and most cultivars, BYDV-PAV was the most prevalent virus species. In the years with high virus incidence, a majority plots with the elevated levels of CO2 (eCO2) were associated with increased levels of virus relative to the plots with ambient CO2. In 2013, 2014 and 2016 the recorded mean percent virus incidence was higher under elevated CO2 when compared to ambient CO2 by 33%, 14% and 34%, respectively. The mechanism behind increased yellow dwarf virus incidence under elevated CO2 is not well understood. Potential factors involved in the higher virus incidence under elevated CO2 conditions are discussed.

Can nitrogen fertiliser maintain wheat (Triticum aestivum) grain protein concentration in an elevated CO2 environment

The effect of different nitrogen (N) management strategies (i.e. N rate; 0, 25, 50, 100u2009kgu2009ha–1, split N application, foliar N application, legume precropping) were assessed for how they may reverse the reduction of grain protein concentration (GPC) under elevated CO2 (eCO2; 550u2009µmolu2009mol–1) of wheat (cv. Yitpi) using the Australian Grains Free Air CO2 Enrichment facility. GPC did not increase significantly under eCO2 for most of the N management strategies assessed when compared with ambient CO2 (aCO2; 390u2009µmolu2009mol–1). Grain yield of cv. Yitpi under aCO2 increased by 43% (Pu2009<u20090.001) with application of 100u2009kgu2009Nu2009ha–1 when compared with 0u2009kgu2009Nu2009ha–1 at sowing; this response was approximately double (82%) when 100u2009kgu2009Nu2009ha–1 was applied under eCO2 conditions. Under aCO2 conditions, by adding 100u2009kgu2009Nu2009ha–1 at sowing, the GPC increased by 37% compared with the GPC at N0; whereas under eCO2 conditions, by adding the same quantity of N fertiliser, the GPC increased by only 28%. The highest level of N applied (100u2009kgu2009ha–1), chosen for economic and practical reasons in a low-rainfall, yield-limiting environment, was lower than that reported in other global studies (250–350u2009kgu2009ha–1). In a low-rainfall, yield-limiting environment, it is not practical to increase GPC by applying N alone; new cultivars may be required if grain growers are to maintain grain protein (and functionality) in the future as CO2 levels continue to increase.

Multimodel ensembles improve predictions of crop–environment–management interactions

A recent innovation in assessment of climate change impact on agricultural production has been to use crop multimodel ensembles (MMEs). These studies usually find large variability between individual models but that the ensemble mean (e-mean) and median (e-median) often seem to predict quite well. However, few studies have specifically been concerned with the predictive quality of those ensemble predictors. We ask what is the predictive quality of e-mean and e-median, and how does that depend on the ensemble characteristics. Our empirical results are based on five MME studies applied to wheat, using different data sets but the same 25 crop models. We show that the ensemble predictors have quite high skill and are better than most and sometimes all individual models for most groups of environments and most response variables. Mean squared error of e-mean decreases monotonically with the size of the ensemble if models are added at random, but has a minimum at usually 2-6 models if best-fit models are added first. Our theoretical results describe the ensemble using four parameters: average bias, model effect variance, environment effect variance, and interaction variance. We show analytically that mean squared error of prediction (MSEP) of e-mean will always be smaller than MSEP averaged over models and will be less than MSEP of the best model if squared bias is less than the interaction variance. If models are added to the ensemble at random, MSEP of e-mean will decrease as the inverse of ensemble size, with a minimum equal to squared bias plus interaction variance. This minimum value is not necessarily small, and so it is important to evaluate the predictive quality of e-mean for each target population of environments. These results provide new information on the advantages of ensemble predictors, but also show their limitations.

Water availability moderates N2 fixation benefit from elevated [CO2]: A 2-year free-air CO2 enrichment study on lentil (Lens culinaris MEDIK.) in a water limited agroecosystem: N2 fixation of lentil under elevated [CO2]

Increased biomass and yield of plants grown under elevated [CO2 ] often corresponds to decreased grain N concentration ([N]), diminishing nutritional quality of crops. Legumes through their symbiotic N2 fixation may be better able to maintain biomass [N] and grain [N] under elevated [CO2 ], provided N2 fixation is stimulated by elevated [CO2 ] in line with growth and yield. In Mediterranean-type agroecosystems, N2 fixation may be impaired by drought, and it is unclear whether elevated [CO2 ] stimulation of N2 fixation can overcome this impact in dry years. To address this question, we grew lentil under two [CO2 ] (ambient ~400xa0ppm and elevated ~550xa0ppm) levels in a free-air CO2 enrichment facility over two growing seasons sharply contrasting in rainfall. Elevated [CO2 ] stimulated N2 fixation through greater nodule number (+27%), mass (+18%), and specific fixation activity (+17%), and this stimulation was greater in the high than in the low rainfall/dry season. Elevated [CO2 ] depressed grain [N] (-4%) in the dry season. In contrast, grain [N] increased (+3%) in the high rainfall season under elevated [CO2 ], as a consequence of greater post-flowering N2 fixation. Our results suggest that the benefit for N2 fixation from elevated [CO2 ] is high as long as there is enough soil water to continue N2 fixation during grain filling.

The water use dynamics of canola cultivars grown under elevated CO2 are linked to their leaf area development

The CO2 fertilisation effect is often predicted to be greater under drier than wetter conditions, mainly due to hypothesised early season water savings under elevated [CO2] (e[CO2]). However, water savings largely depend on the balance between CO2-induced improvement of leaf-level water use efficiency and CO2-stimulation of transpiring leaf area. The dynamics of water use during the growing season can therefore vary depending on leaf area development. Two canola (Brassica napus L.) cultivars of contrasting growth and vigour (vigorous hybrid cv. Hyola 50 and non-hybrid cv. Thumper) were grown under ambient [CO2] (a[CO2], ∼400u2009μmolu2009mol-1) or e[CO2] (∼700u2009μmolu2009mol-1) with two water treatments (well-watered and mild drought) in a glasshouse to investigate the interdependence of leaf area development and water use. Dynamics of water use during the growing season varied depending on [CO2] and cultivars. Early stimulation of leaf growth under e[CO2], which also depended on cultivar, overcompensated for the effect of increased leaf-level water use efficiency, so that weekly water use was greater and water depletion from soil greater under e[CO2] than a[CO2]. This result shows that the balance between leaf area and water use efficiency stimulation by e[CO2] can tip towards early depletion of available soil water, so that e[CO2] does not lead to water savings, and the CO2 fertilisation effect is not greater under drier conditions.