ARC Centre of Excellence in Translational Photosynthesis, Division of Plant Science, Research School of Biology, The Australian National University, Canberra, Australian Capital Territory, Australia.
School of Biological Sciences, University of Tasmania, Hobart, Tasmania, Australia.
Nat Plants. 2020 Sep;6(9):1116-1125. doi: 10.1038/s41477-020-00760-6. Epub 2020 Sep 7.
Tight coordination in the photosynthetic, gas exchange and water supply capacities of leaves is a globally conserved trend across land plants. Strong selective constraints on leaf carbon gain create the opportunity to use quantitative optimization theory to understand the connected evolution of leaf photosynthesis and water relations. We developed an analytical optimization model that maximizes the long-term rate of leaf carbon gain, given the carbon costs in building and maintaining stomata, leaf hydraulics and osmotic pressure. Our model demonstrates that selection for optimal gain should drive coordination between key photosynthetic, gas exchange and water relations traits. It also provides predictions of adaptation to drought and the relative costs of key leaf functional traits. Our results show that optimization in terms of carbon gain, given the carbon costs of physiological traits, successfully unites leaf photosynthesis and water relations and provides a quantitative framework to consider leaf functional evolution and adaptation.
叶片光合作用、气体交换和水分供应能力的紧密协调是陆地植物在全球范围内普遍存在的趋势。叶片碳获取的强烈选择约束为利用定量优化理论来理解叶片光合作用和水分关系的协同进化创造了机会。我们开发了一种分析优化模型，该模型在考虑构建和维持气孔、叶片水力和渗透压的碳成本的情况下，使叶片碳获取的长期速率最大化。我们的模型表明，为了获得最佳收益而进行的选择应该促使关键光合作用、气体交换和水分关系特性之间的协调。它还提供了对干旱适应和关键叶片功能特性相对成本的预测。我们的研究结果表明，在考虑到生理特性的碳成本的情况下，以碳获取为优化目标，可以成功地将叶片光合作用和水分关系结合起来，并提供了一个定量框架来考虑叶片功能进化和适应。
