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Crop Models

Evaluating the CROPGRO–Soybean Model Ability to Simulate Photosynthesis Response to Carbon Dioxide Levels

^a Dep. of Agronomy, Univ. of Florida, Gainesville, FL 32611-0500
^b USDA-ARS and Dep. of Agronomy, Univ. of Florida, Gainesville, FL 32611-0965
^c Dep. of Agricultural and Biological Engineering, Univ. of Florida, Gainesville, FL 32611-0570. Florida Agric. Exp. Stn. Journal Ser. no. R-10598

^* Corresponding author (alagarsw{at}msu.edu)

Received for publication December 6, 2004. Atmospheric carbon dioxide concentration [CO₂] will increase in the future and will affect global climate and ecosystem productivity. Crop models used in past assessments of climate change effect on ecosystem productivity have not been adequately tested for the ability to simulate ecosystem responses to [CO₂]. Our objective was to evaluate the ability of the default CROPGRO–Soybean model to predict the responses of net leaf photosynthesis (A) and canopy photosynthesis (A_can) to photosynthetic photon flux (PPF) at different [CO₂]. We also compared the default leaf photosynthesis equations in CROPGRO with the full Farquhar equations for ability to predict the response of A to [CO₂]. Simulated and observed A and A_can were light saturated at 800 µmol m^–2 s^–1 PPF at ambient [CO₂] but did not light saturate at PPF >1100 µmol m^–2 s^–1 at elevated [CO₂]. Observed and simulated A responded asymptotically to increasing intercellular [CO₂]. The CROPGRO default photosynthesis equations and the Farquhar equations simulated A equally well at all [CO₂]. Doubled [CO₂] increased simulated A by 52% and A_can by 42%; these values are close to the increases of 39 to 48% for A and 59% for A_can reported in the literature. Root mean square errors for simulated A and A_can were low, and Willmott's index of agreement ranged from 0.86 to 0.99, confirming that the CROPGRO model with default photosynthesis equations can be used to evaluate potential effects of [CO₂] on soybean photosynthesis and productivity.

Abbreviations: LAI, leaf area index • MSE, mean squared error • MSE_s, systematic mean squared error • MSE_u, unsystematic mean squared error • PPF, photosynthetic photon flux • QE, quantum efficiency • RuBP, ribulose 1,5 bisphosphate • RMSE, root mean squared error