Towards a statistically robust determination of minimum water potential and hydraulic risk in plants.

Minimum water potential (Ψ ) is a key variable for characterizing dehydration tolerance and hydraulic safety margins (HSMs) in plants. Ψ is usually estimated as the absolute minimum tissue Ψ experienced by a species, but this is problematic because sample extremes are affected by sample size and the underlying probability distribution. We compare alternative approaches to estimate Ψ and assess the corresponding uncertainties and biases; propose statistically robust estimation methods based on extreme value theory (EVT); and assess the implications of our results for the characterization of hydraulic risk. Our results show that current estimates of Ψ and HSMs are biased, as they are strongly affected by sample size. Because sampling effort is generally higher for species living in dry environments, the differences in current Ψ estimates between these species and those living under milder conditions are partly artefactual. When this bias is corrected using EVT methods, resulting HSMs tend to increase substantially with resistance to embolism across species. Although data availability and representativeness remain the main challenges for proper determination of Ψ , a closer look at Ψ distributions and the use of statistically robust methods to estimate Ψ opens new ground for characterizing plant hydraulic risks.