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一种描述大气 CO2 对叶片光合作用和蒸腾作用影响的气孔优化理论。

A stomatal optimization theory to describe the effects of atmospheric CO2 on leaf photosynthesis and transpiration.

机构信息

Nicholas School of the Environment, Box 90328, Duke University, Durham, NC 27708, USA.

出版信息

Ann Bot. 2010 Mar;105(3):431-42. doi: 10.1093/aob/mcp292. Epub 2009 Dec 8.

Abstract

BACKGROUND AND AIMS

Global climate models predict decreases in leaf stomatal conductance and transpiration due to increases in atmospheric CO2. The consequences of these reductions are increases in soil moisture availability and continental scale run-off at decadal time-scales. Thus, a theory explaining the differential sensitivity of stomata to changing atmospheric CO2 and other environmental conditions must be identified. Here, these responses are investigated using optimality theory applied to stomatal conductance.

METHODS

An analytical model for stomatal conductance is proposed based on: (a) Fickian mass transfer of CO2 and H2O through stomata; (b) a biochemical photosynthesis model that relates intercellular CO2 to net photosynthesis; and (c) a stomatal model based on optimization for maximizing carbon gains when water losses represent a cost. Comparisons between the optimization-based model and empirical relationships widely used in climate models were made using an extensive gas exchange dataset collected in a maturing pine (Pinus taeda) forest under ambient and enriched atmospheric CO2. Key Results and Conclusion In this interpretation, it is proposed that an individual leaf optimally and autonomously regulates stomatal opening on short-term (approx. 10-min time-scale) rather than on daily or longer time-scales. The derived equations are analytical with explicit expressions for conductance, photosynthesis and intercellular CO2, thereby making the approach useful for climate models. Using a gas exchange dataset collected in a pine forest, it is shown that (a) the cost of unit water loss lambda (a measure of marginal water-use efficiency) increases with atmospheric CO2; (b) the new formulation correctly predicts the condition under which CO2-enriched atmosphere will cause increasing assimilation and decreasing stomatal conductance.

摘要

背景与目的

全球气候模型预测,由于大气 CO2 增加,叶片气孔导度和蒸腾作用会降低。这些减少的后果是,在几十年的时间尺度上,土壤湿度的可用性和大陆尺度的径流量会增加。因此,必须确定一种能够解释气孔对不断变化的大气 CO2 和其他环境条件的敏感性差异的理论。在这里,使用应用于气孔导度的最优化理论来研究这些响应。

方法

基于以下方面提出了气孔导度的分析模型:(a) 通过气孔的 CO2 和 H2O 的菲克扩散;(b) 将胞间 CO2 与净光合作用联系起来的生化光合作用模型;(c) 基于优化的气孔模型,当水分损失代表成本时,最大程度地提高碳增益。使用在大气 CO2 背景和富集条件下收集的成熟松树(Pinus taeda)林的广泛气体交换数据集,对基于优化的模型与广泛用于气候模型的经验关系进行了比较。

主要结果和结论

在这种解释中,提出单个叶片可以在短期(约 10 分钟时间尺度)而不是在日常或更长时间尺度上自主调节气孔开度以达到最优状态。推导出的方程是解析的,具有明确的导度、光合作用和胞间 CO2 的表达式,因此该方法对气候模型很有用。使用在松林收集的气体交换数据集,结果表明:(a) 单位水分损失 lambda 的成本(衡量边际用水效率的指标)随大气 CO2 增加而增加;(b) 新公式正确预测了 CO2 富集大气将导致同化增加和气孔导度降低的条件。

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