Plant water potential improves prediction of empirical stomatal models

William R.L. Anderegg, Adam Wolf, Adriana Arango-Velez, Brendan Choat, Daniel J. Chmura, Steven Jansen, Thomas E Kolb, Shan Li, Frederick Meinzer, Pilar Pita, Víctor Resco de Dios, John S. Sperry, Brett T. Wolfe, Stephen Pacala

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

Original languageEnglish (US)
Article numbere0185481
JournalPLoS One
Volume12
Issue number10
DOIs
StatePublished - Oct 1 2017

Fingerprint

water potential
Droughts
Ecosystem
Drought
prediction
Water
drought
ecosystems
Ecosystems
stomatal conductance
Climate Change
Climate
Dehydration
soil water potential
leaf water potential
woody plants
Climate change
Soil
water stress
climate change

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Anderegg, W. R. L., Wolf, A., Arango-Velez, A., Choat, B., Chmura, D. J., Jansen, S., ... Pacala, S. (2017). Plant water potential improves prediction of empirical stomatal models. PLoS One, 12(10), [e0185481]. https://doi.org/10.1371/journal.pone.0185481

Plant water potential improves prediction of empirical stomatal models. / Anderegg, William R.L.; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J.; Jansen, Steven; Kolb, Thomas E; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S.; Wolfe, Brett T.; Pacala, Stephen.

In: PLoS One, Vol. 12, No. 10, e0185481, 01.10.2017.

Research output: Contribution to journalArticle

Anderegg, WRL, Wolf, A, Arango-Velez, A, Choat, B, Chmura, DJ, Jansen, S, Kolb, TE, Li, S, Meinzer, F, Pita, P, Resco de Dios, V, Sperry, JS, Wolfe, BT & Pacala, S 2017, 'Plant water potential improves prediction of empirical stomatal models', PLoS One, vol. 12, no. 10, e0185481. https://doi.org/10.1371/journal.pone.0185481
Anderegg WRL, Wolf A, Arango-Velez A, Choat B, Chmura DJ, Jansen S et al. Plant water potential improves prediction of empirical stomatal models. PLoS One. 2017 Oct 1;12(10). e0185481. https://doi.org/10.1371/journal.pone.0185481
Anderegg, William R.L. ; Wolf, Adam ; Arango-Velez, Adriana ; Choat, Brendan ; Chmura, Daniel J. ; Jansen, Steven ; Kolb, Thomas E ; Li, Shan ; Meinzer, Frederick ; Pita, Pilar ; Resco de Dios, Víctor ; Sperry, John S. ; Wolfe, Brett T. ; Pacala, Stephen. / Plant water potential improves prediction of empirical stomatal models. In: PLoS One. 2017 ; Vol. 12, No. 10.
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