Intra-Specific Variability in Plant Hydraulic Parameters Inferred From Model Inversion of Sap Flux Data

Yaojie Lu, Brandon Sloan, Sally E. Thompson, Alexandra G. Konings, Gil Bohrer, Ashley Matheny, Xue Feng

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1 Scopus citations


Understanding plant hydraulic regulation is critical for predicting plant and ecosystem responses to projected increases in drought stress. Plant hydraulic regulation is controlled by observable, diverse plant hydraulic traits that can vary as much across individuals of the same species as they do across different species. Direct measurements of plant hydraulic traits from a range of ecosystems remain limited in comparison to other, more readily measured traits (e.g., specific leaf area). Furthermore, plant hydraulic trait measurements, often made at leaf or branch levels, are not easily scaled to whole-plant values that are typically used to predict plant and ecosystem fluxes. In this study, multiple whole-plant hydraulic parameters are inferred from observations of plant water use (i.e., sap flow), soil properties, and meteorological data. We use a Markov Chain Monte Carlo model inversion approach to obtain the best estimates and uncertainty of plant hydraulic parameters that capture whole-plant effective embolism resistance and stomatal sensitivity to decreasing plant water potential. We then use the inferred values in the model to estimate whole-tree water use and isohydricity. This approach reliably infers whole-plant parameter values with enough specificity to resolve inter- and intra-specific differences, and thus supplements time- and labor-intensive direct measurements of traits.

Original languageEnglish (US)
Article numbere2021JG006777
JournalJournal of Geophysical Research: Biogeosciences
Issue number6
StatePublished - Jun 2022

Bibliographical note

Funding Information:
Funding for US‐UMB AmeriFlux core site was provided by the U.S. Department of Energy's Office of Science. Sap flux observations in US‐UMB were funded by NSF award 1521238. The authors thank Jesse Hahm and Yanlan Liu for insightful discussions and suggestions during the course of this project. Special thanks are also due to the Minnesota Supercomputer Institute computing facilities. A.M. was supported by the US Department of Energy TES grant DE‐SC0020116 and the US National Science Foundation EAR CAREER award #2046768. A.G.K. was supported by NSF DEB award 1942133 and by NASA Carbon Cycle Science Grant 80NSSC21K1712. X.F. and B.S. were supported by NSF DEB award 2045610. G.B. was supported by BARD award IS‐5304‐20.

Publisher Copyright:
© 2022. The Authors.


  • MCMC
  • model inversion
  • plant hydraulics
  • sap flow
  • xylem vulnerability


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