Hierarchical statistical modeling of xylem vulnerability to cavitation: Methods

Kiona Ogle, Jarrett J. Barber, Cynthia Willson, Brenda Thompson

Research output: Contribution to journalArticlepeer-review

53 Scopus citations


Cavitation of xylem elements diminishes the water transport capacity of plants, and quantifying xylem vulnerability to cavitation is important to understanding plant function. Current approaches to analyzing hydraulic conductivity (K) data to infer vulnerability to cavitation suffer from problems such as the use of potentially unrealistic vulnerability curves, difficulty interpreting parameters in these curves, a statistical framework that ignores sampling design, and an overly simplistic view of uncertainty. This study illustrates how two common curves (exponential-sigmoid and Weibull) can be reparameterized in terms of meaningful parameters: maximum conductivity (k sat), water potential (-P) at which percentage loss of conductivity (PLC) = X% (PX), and the slope of the PLC curve at PX (SX), a 'sensitivity' index. We provide a hierarchical Bayesian method for fitting the reparameterized curves to KH data. We illustrate the method using data for roots and stems of two populations of Juniperus scopulorum and test for differences in ksat, PX, and SX between different groups. Two important results emerge from this study. First, the Weibull model is preferred because it produces biologically realistic estimates of PLC near P = 0 MPa. Second, stochastic embolisms contribute an important source of uncertainty that should be included in such analyses.

Original languageEnglish (US)
Pages (from-to)541-554
Number of pages14
JournalNew Phytologist
Issue number2
StatePublished - Apr 2009
Externally publishedYes


  • Bayesian statistics
  • Cavitation
  • Embolism
  • Hierarchical Bayes
  • Hydraulic conductivity
  • Juniperus scopulorum (Rocky Mountain juniper)
  • Vulnerability curve

ASJC Scopus subject areas

  • Physiology
  • Plant Science


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