Paper of the Month December 2017

Do all leaf photosynthesis parameters of rice acclimate to elevated CO2, elevated temperature, and their combination, in FACE environments?


Leaf photosynthesis of crops acclimates to elevated CO2 and temperature, but studies quantifying responses of leaf photosynthetic parameters to combined CO2 and temperature increases under field conditions are scarce. We measured leaf photosynthesis of rice cultivars Changyou 5 and Nanjing 9108 grown in two free-air CO2 enrichment (FACE) systems, respectively, installed in paddy fields. Each FACE system had four combinations of two levels of CO2 (ambient and enriched) and two levels of canopy temperature (no warming and warmed by 1.0–2.0°C). Parameters of the C3 photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model), and of a stomatal conductance (gs) model were estimated for the four conditions. Most photosynthetic parameters acclimated to elevated CO2, elevated temperature, and their combination. The combination of elevated CO2 and temperature changed the functional relationships between biochemical parameters and leaf nitrogen content for Changyou 5. The gs model significantly underestimated gs under the combination of elevated CO2 and temperature by 19% for Changyou 5 and by 10% for Nanjing 9108 if no acclimation was assumed. However, our further analysis applying the coupled gs–FvCB model to an independent, previously published FACE experiment showed that including such an acclimation response of gs hardly improved prediction of leaf photosynthesis under the four combinations of CO2 and temperature. Therefore, the typical procedure that crop models using the FvCB and gs models are parameterized from plants grown under current ambient conditions may not result in critical errors in projecting productivity of paddy rice under future global change.

Chuang Cai, Gang Li, Hailong Yang, Jiaheng Yang, Hong Liu, Paul C. Struik, Weihong Luo, Xinyou Yin, Lijun Di, Xuanhe Guo, Wenyu Jiang, Chuanfei Si, Genxing Pan and Jianguo Zhu (2017) Global Change Biology (online first)

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