Hydraulic trade-offs and space filling enable better predictions of vascular structure and function in plants
Hydraulic trade-offs and space filling enable better predictions of vascular structure and function in plants
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DOI：
10.1073/pnas.1012194108
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发表时间：
2010-12-28
影响因子：
11.1
通讯作者：
von Allmen, E. I.
中科院分区：
文献类型：
--
作者：
Savage, V. M.;Bentley, L. P.;von Allmen, E. I.
植物维管网络是植物形态、功能和多样性的核心。在这里，我们开发了一种植物网络缩放理论，该理论基于血管系统的最佳空间填充以及水力安全和效率之间的权衡。包括这些进化驱动因素，可以预测汁液流动、木质部导管从主干到末梢的半径锥度，以及木质部导管的频率如何随导管半径变化。为了验证我们的预测，我们对枫树、橡树和松树进行了全面的实证测量，并对广泛的树种进行了补充文献数据。对我们的植物网络模型进行的强大的种内和种间评估表明，观察到的尺度特性的集中趋势比West， Brown和Enquist （WBE）或管道模型更支持我们的预测。因此，我们的模型比现有的网络模型更准确地描述了维管结构，应该用作理解和预测单个植物到整个森林的尺度的基线。此外，我们的模型足够灵活，可以围绕网络设计规则对物种变化进行量化。这些结果表明，我们提出的进化驱动因素是决定植物物种内部和物种间生理过程如何扩展的基础。
Plant vascular networks are central to botanical form, function, and diversity. Here, we develop a theory for plant network scaling that is based on optimal space filling by the vascular system along with trade-offs between hydraulic safety and efficiency. Including these evolutionary drivers leads to predictions for sap flow, the taper of the radii of xylem conduits from trunk to terminal twig, and how the frequency of xylem conduits varies with conduit radius. To test our predictions, we use comprehensive empirical measurements of maple, oak, and pine trees and complementary literature data that we obtained for a wide range of tree species. This robust intra-and interspecific assessment of our botanical network model indicates that the central tendency of observed scaling properties supports our predictions much better than the West, Brown, and Enquist (WBE) or pipe models. Consequently, our model is a more accurate description of vascular architecture than what is given by existing network models and should be used as a baseline to understand and to predict the scaling of individual plants to whole forests. In addition, our model is flexible enough to allow the quantification of species variation around rules for network design. These results suggest that the evolutionary drivers that we propose have been fundamental in determining how physiological processes scale within and across plant species.