Research School of Biology, Australian National University, Canberra, Australian Capital Territory, 2601 Australia
College of Science and Engineering, James Cook University, Cairns, Queensland, 4870 Australia.
Plant Physiol. 2019 Nov;181(3):1175-1190. doi: 10.1104/pp.19.00633. Epub 2019 Sep 13.
Theoretical models of photosynthetic isotopic discrimination of CO (C and O) are commonly used to estimate mesophyll conductance ( ). This requires making simplifying assumptions and assigning parameter values so that can be solved for as the residual term. Uncertainties in estimation occur due to measurement noise and assumptions not holding, including parameter uncertainty and model parametrization. Uncertainties in the C model have been explored previously, but there has been little testing undertaken to determine the reliability of estimates from the O model ( ). In this study, we exploited the action of carbonic anhydrase in equilibrating CO with leaf water and manipulated the observed photosynthetic discrimination (ΔO) by changing the oxygen isotopic composition of the source gas CO and water vapor. We developed a two-source δO method, whereby two measurements of ΔO were obtained for a leaf with its gas-exchange characteristics otherwise unchanged. Measurements were performed in broad bean () and Algerian oak () in response to light and vapor pressure deficit. Despite manipulating the ΔO by over 100‰, in most cases we observed consistency in the calculated , providing confidence in the measurements and model theory. Where there were differences in estimates between source-gas measurements, we explored uncertainty associated with two model assumptions (the isotopic composition of water at the sites of CO-water exchange, and the humidity of the leaf internal airspace) and found evidence for both. Finally, we provide experimental guidelines to minimize the sensitivity of estimates to measurement errors. The two-source δO method offers a flexible tool for model parameterization and provides an opportunity to refine our understanding of leaf water and CO fluxes.
光合碳氧同位素分馏的理论模型(C 和 O)通常用于估计叶肉导度()。这需要进行简化假设并分配参数值,以便将作为残差项求解。由于测量噪声和假设不成立,会导致估计中的不确定性,包括参数不确定性和模型参数化。之前已经探讨了 C 模型中的不确定性,但对于 O 模型()中估计的可靠性,很少进行测试。在这项研究中,我们利用碳酸酐酶在使 CO 与叶水达到平衡方面的作用,并通过改变源气体 CO 和水蒸气的氧同位素组成来操纵观察到的光合同位素分馏(ΔO)。我们开发了一种双源 δO 方法,通过该方法可以在不改变叶片气体交换特性的情况下,对叶片进行两次 ΔO 测量。在宽叶蚕豆()和阿尔及利亚栎()中进行了测量,以响应光和蒸气压亏缺。尽管通过超过 100‰来操纵 ΔO,但在大多数情况下,我们观察到计算出的的一致性,从而对测量和模型理论有信心。在源气测量中存在 估计差异的情况下,我们探讨了与两个模型假设(CO-水交换位点的水的同位素组成和叶片内部气腔的湿度)相关的不确定性,并找到了证据。最后,我们提供了实验指南,以最大程度地减少对测量误差的敏感性。双源 δO 方法为模型参数化提供了一种灵活的工具,并提供了一个机会来完善我们对叶片水和 CO 通量的理解。