Chlorophyll Can Be Reduced in Crop Canopies with Little Penalty to Photosynthesis.

The hypothesis that reducing chlorophyll content (Chl) can increase canopy photosynthesis in soybeans was tested using an advanced model of canopy photosynthesis. The relationship among leaf Chl, leaf optical properties, and photosynthetic biochemical capacity was measured in 67 soybean (Glycine max) accessions showing large variation in leaf Chl. These relationships were integrated into a biophysical model of canopy-scale photosynthesis to simulate the intercanopy light environment and carbon assimilation capacity of canopies with wild type, a Chl-deficient mutant (Y11y11), and 67 other mutants spanning the extremes of Chl to quantify the impact of variation in leaf-level Chl on canopy-scale photosynthetic assimilation and identify possible opportunities for improving canopy photosynthesis through Chl reduction. These simulations demonstrate that canopy photosynthesis should not increase with Chl reduction due to increases in leaf reflectance and nonoptimal distribution of canopy nitrogen. However, similar rates of canopy photosynthesis can be maintained with a 9% savings in leaf nitrogen resulting from decreased Chl. Additionally, analysis of these simulations indicate that the inability of Chl reductions to increase photosynthesis arises primarily from the connection between Chl and leaf reflectance and secondarily from the mismatch between the vertical distribution of leaf nitrogen and the light absorption profile. These simulations suggest that future work should explore the possibility of using reduced Chl to improve canopy performance by adapting the distribution of the "saved" nitrogen within the canopy to take greater advantage of the more deeply penetrating light.

Simultaneous improvement in productivity, water use, and albedo through crop structural modification.

Spanning 15% of the global ice-free terrestrial surface, agricultural lands provide an immense and near-term opportunity to address climate change, food, and water security challenges. Through the computationally informed breeding of canopy structural traits away from those of modern cultivars, we show that solutions exist that increase productivity and water use efficiency, while increasing land-surface reflectivity to offset greenhouse gas warming. Plants have evolved to maximize capture of radiation in the upper leaves, thus shading competitors. While important for survival in the wild, this is suboptimal in monoculture crop fields for maximizing productivity and other biogeophysical services. Crop progenitors evolved over the last 25 million years in an atmosphere with less than half the [CO2] projected for 2050. By altering leaf photosynthetic rates, rising [CO2] and temperature may also alter the optimal canopy form. Here using soybean, the world's most important protein crop, as an example we show by applying optimization routines to a micrometeorological leaf canopy model linked to a steady-state model of photosynthesis, that significant gains in production, water use, and reflectivity are possible with no additional demand on resources. By modifying total canopy leaf area, its vertical profile and angular distribution, and shortwave radiation reflectivity, all traits available in most major crop germplasm collections, increases in productivity (7%) are possible with no change in water use or albedo. Alternatively, improvements in water use (13%) or albedo (34%) can likewise be made with no loss of productivity, under Corn Belt climate conditions.

Implications for the hydrologic cycle under climate change due to the expansion of bioenergy crops in the Midwestern United States.

To meet emerging bioenergy demands, significant areas of the large-scale agricultural landscape of the Midwestern United States could be converted to second generation bioenergy crops such as miscanthus and switchgrass. The high biomass productivity of bioenergy crops in a longer growing season linked tightly to water use highlight the potential for significant impact on the hydrologic cycle in the region. This issue is further exacerbated by the uncertainty in the response of the vegetation under elevated CO(2) and temperature. We use a mechanistic multilayer canopy-root-soil model to (i) capture the eco-physiological acclimations of bioenergy crops under climate change, and (ii) predict how hydrologic fluxes are likely to be altered from their current magnitudes. Observed data and Monte Carlo simulations of weather for recent past and future scenarios are used to characterize the variability range of the predictions. Under present weather conditions, miscanthus and switchgrass utilized more water than maize for total seasonal evapotranspiration by approximately 58% and 36%, respectively. Projected higher concentrations of atmospheric CO(2) (550 ppm) is likely to decrease water used for evapotranspiration of miscanthus, switchgrass, and maize by 12%, 10%, and 11%, respectively. However, when climate change with projected increases in air temperature and reduced summer rainfall are also considered, there is a net increase in evapotranspiration for all crops, leading to significant reduction in soil-moisture storage and specific surface runoff. These results highlight the critical role of the warming climate in potentially altering the water cycle in the region under extensive conversion of existing maize cropping to support bioenergy demand.