College of Agriculture, Nanjing Agricultural University, Nanjing, Jiangsu, PR China.
Centre for Crop Systems Analysis, Department of Plant Sciences, Wageningen University & Research, Wageningen, The Netherlands.
Glob Chang Biol. 2020 Feb;26(2):539-556. doi: 10.1111/gcb.14830. Epub 2019 Oct 17.
Crops show considerable capacity to adjust their photosynthetic characteristics to seasonal changes in temperature. However, how photosynthesis acclimates to changes in seasonal temperature under future climate conditions has not been revealed. We measured leaf photosynthesis (A ) of wheat (Triticum aestivum L.) and rice (Oryza sativa L.) grown under four combinations of two levels of CO (ambient and enriched up to 500 µmol/mol) and two levels of canopy temperature (ambient and increased by 1.5-2.0°C) in temperature by free-air CO enrichment (T-FACE) systems. Parameters of a biochemical C -photosynthesis model and of a stomatal conductance (g ) model were estimated for the four conditions and for several crop stages. Some biochemical parameters related to electron transport and most g parameters showed acclimation to seasonal growth temperature in both crops. The acclimation response did not differ much between wheat and rice, nor among the four treatments of the T-FACE systems, when the difference in the seasonal growth temperature was accounted for. The relationships between biochemical parameters and leaf nitrogen content were consistent across leaf ranks, developmental stages, and treatment conditions. The acclimation had a strong impact on g model parameters: when parameter values of a particular stage were used, the model failed to correctly estimate g values of other stages. Further analysis using the coupled g -biochemical photosynthesis model showed that ignoring the acclimation effect did not result in critical errors in estimating leaf photosynthesis under future climate, as long as parameter values were measured or derived from data obtained before flowering.
作物具有相当大的能力来调整其光合作用特性以适应季节性温度变化。然而,在未来气候条件下,光合作用如何适应季节性温度变化尚未揭示。我们在温度自由空气 CO2 富集(T-FACE)系统中测量了小麦(Triticum aestivum L.)和水稻(Oryza sativa L.)在两种 CO2 水平(环境和富集至 500 µmol/mol)和两种冠层温度水平(环境和增加 1.5-2.0°C)的四个组合下的叶片光合作用(A)。为四个条件和几个作物阶段估算了生化 C-光合作用模型和气孔导度(g)模型的参数。在两种作物中,与电子传递有关的一些生化参数和大多数 g 参数都适应了季节性生长温度。当考虑季节性生长温度的差异时,小麦和水稻之间以及 T-FACE 系统的四个处理之间的适应反应差异不大。在整个叶片等级、发育阶段和处理条件下,生化参数与叶片氮含量之间的关系都是一致的。适应对 g 模型参数有很大影响:当使用特定阶段的参数值时,模型无法正确估计其他阶段的 g 值。使用耦合 g-生化光合作用模型的进一步分析表明,只要参数值是从开花前获得的数据中测量或推导出来的,那么忽略适应效应并不会导致在未来气候下估计叶片光合作用出现重大错误。