Effects of elevated CO2 and temperature on soybean growth and gas exchange rates: a modified GLYCIM model

Authors: SUN, WENGUANG - University Of Nebraska; Fleisher, David; Timlin, Dennis; LI, SANAI - Us Forest Service (FS); WANG, ZHUANGJI - University Of Maryland; Reddy, Vangimalla

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/22/2021
Publication Date: 11/7/2021
Citation: Sun, W., Fleisher, D.H., Timlin, D.J., Li, S., Wang, Z., Reddy, V. 2021. Effects of elevated CO2 and temperature on soybean growth and gas exchange rates: a modified GLYCIM model. Agricultural and Forest Meteorology. 197:106980. https://doi.org/10.1016/j.agrformet.2021.108700.
DOI: https://doi.org/10.1016/j.agrformet.2021.108700

Interpretive Summary: Global surface air temperature and atmospheric carbon dioxide (CO2) concentrations are concomitantly rising. Understanding how these variables influence soybean photosynthesis and transpiration is very important so that scientists can accurately predict potential climate change impacts on yield. Many scientific tools are used to simulate these impacts, but the quality of these predictions needs to be improved. The current research focused on improving an existing mathematical model for soybean by replacing some of the older equations with new state-of-the-art ones. Experimental data was used to test and evaluate the improvements to this model. Statistical metrics were used to determine how well these changes increased the model accuracy. These showed the new model was able to simulate photosynthesis and transpiration considerably better than the old model. This result improves the confidence that scientists have when identifying impacts of climate changes on soybean production. The new improved modal can assist farmers to identify optimal management strategies in response.

Technical Abstract: GLYCIM is a comprehensive soybean crop simulator that simulates soil, plant, and atmospheric linkages at the physical and physiological process level. In order to more accurately simulate canopy photosynthesis and growth processes under climate change conditions, the current research focused on replacing the original photosynthesis equation with a leaf-level coupled model for photosynthesis, transpiration, and stomatal conductance with an energy balance. Soybean gas exchange and plant growth data from six SPAR (soil -plant -atmosphere research) chamber experiments at four temperature treatments (24/18oC, 28/22oC, 32/26oC, and 36/30oC, respectively) under ambient (457 µmol mol-1) CO2 levels and two temperature treatments (28/32oC and 32/26oC, respectively) under elevated (670 µmol mol-1) CO2 conditions were used to evaluate the ability of two GLYCIM model versions, original and modified, for simulating the responses of canopy photosynthesis, transpiration rates and observed harvest data. Simulation results showed that modified GLYCIM with coupled models had significantly better agreement with observed canopy photosynthetic and transpiration rates, as exhibited by the higher values of IA (seasonal photosynthesis, average 0.86 versus 0.82; transpiration, average 0.95 versus 0.84) and lower values of RMSE (seasonal photosynthesis, average 0.58 versus 0.64 mol CO2 m-2 season-1; transpiration, average 1.99 versus 3.16 mmol H2O m-2 s-1) when compared to the original GLYCIM. The simulation of carbon partitioning to stems, leaves, pod and seed were reasonably accurate for both versions (IA = 0.97), although leaf and stem growth were under-predicted at warmest temperature treatments at either CO2 level. Overall, the modified GLYCIM provided an improved fit of gas exchange and harvest data over a broad range of temperatures and CO2 levels and will be useful to develop adaptation responses for projected warmer, CO2 enriched, climate.