Simulating water transport through complex leaf venation network architectures

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Ilaine Silveira Matos, ESPM, Postdoctoral Researcher, Berkeley, CA, Hailey J. Park, University of California Berkeley, Berkeley, CA, Hailey J. Park, Srinivasan Madhavan and Satvik Sharma, ESPM, Undergraduate student, Berkeley, CA, Luiza Maria Aparecido, School of Earth and Space Exploration, Arizona State University, Tempe, AZ, USA, Mark Fricker, Department of Plant Sciences, University of Oxford, Oxford, United Kingdom, Mickey Boakye, ESPM, PhD student, Berkeley, CA, Nathan A. Nguyen, School of Life Sciences, Undergraduate student, Tempe, AZ, Benjamin Blonder, ESPM, University of California Berkeley, Berkeley, CA

Background/Question/Methods
Plant species greatly vary in their rate of leaf water transport (i.e. leaf hydraulic conductance, Kleaf), which may influence photosynthetic capacity and drought response. Elucidating the ecophysiological processes that drive Kleaf interspecific variation is challenging, as Kleaf may be influenced by several macroscopic (e.g. venation network architecture) and microscopic properties (e.g. vein packing, leakage degree and mesophyll resistivity). The current methods available to measure Kleaf are unable to simultaneously investigate those different properties, their interaction, and their responsiveness to changing conditions. Moreover, it has been difficult to accurately measure the venation network architecture for whole leaves. Here, we propose a new electrical analog model, which uses the entire leaf venation network (extracted by machine learning methods) to simulate Kleaf, and to explore the underlying mechanisms for its variation. In this approach, each vein in the leaf network is converted into a resistor in an electronic circuit, then a circuit simulator software (Ngspice and Rspice) is used to estimate the total Kleaf. Lastly, Approximate Bayesian Computation is applied to explore which values of the three leaf properties (vein package – VP; vein leakage – VL; and mesophyll resistivity - MR) are most consistent with the observed Kleaf values.
Results/Conclusions
Our new model was able to estimate Kleaf of 14 species (with disparate vein network architectures), with an average discrepancy of 8% between modeled and experimentally measured Kleaf. The modelled Kleaf increased with increasing VL and decreasing MR and VP. Leaves were more efficient in transporting water when their xylem vessels were leakier, less closely packed inside the veins, and when the mesophyll cells imposed less resistance to water flow. Preliminary results indicate that VL and VP play a more important role in determining Kleaf variation than MR. Within each species, VL and VP correlated positively, but they did not co-varied with MR. Therefore, that having more densely packed veins limited the leaf’s ability to leak only through the minor veins. The effects of macroscopic properties on Kleaf are still being modelled. Our approach is an important step towards a more realistic model that explicitly accounts for macro and microstructural properties to better understand how water flows though leaves. The model has flexibility and potential to further include varying conditions and disturbances, such as drier conditions and vein obstruction/damage.