BER launches Environmental System Science Program. Visit our new website under construction!

U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Plant Water Potential Improves Prediction of Empirical Stomatal Models
Published: October 12, 2017
Posted: June 26, 2018

The Science 
A recent study found that current leaf-level empirical models overpredict stomatal conductance during drought conditions, and a recently proposed model improves predictions during drought conditions.

The Impact
Including the impairment of soil-to-leaf water transport will improve predictions of stomatal conductance during drought conditions. Many biomes contain a diversity of plant stomatal strategies during water stress.

Summary
Ecosystem models rely on empirical relationships to predict stomatal responses to changing environmental conditions, but these are not well tested during drought conditions. Scientists from the University of Utah, in conjunction with the Next-Generation Ecosystem Experiments (NGEE)–Tropics project, compiled datasets of stomatal conductance and leaf water potential for 34 woody plant species that span global forest biomes. They tested how well three major stomatal models and a recently proposed model predicted measured stomatal conductance. They found that current models consistently overpredicted stomatal conductance during dry conditions, whereas the recently proposed model, which includes loss of hydraulic transport capacity, improved predictions compared to current models, particularly during droughts. These results also show that many biomes contain a diversity of plant stomatal strategies during water stress. Such improvements in stomatal simulation will help to predict the response of ecosystems to future climate extremes.

Contacts
BER Program Managers
Daniel Stover
Terrestrial Ecosystem Science, SC-23.1
Daniel.Stover@science.doe.gov (301-903-0289)

Dorothy Koch
SC-23.1
Dorothy.Koch@science.doe.gov (301-903-0105)

Principal Investigator
William R. L. Anderegg
University of Utah
Salt Lake City, UT 84112
anderegg@utah.edu

Funding
Funding for this research was provided by National Science Foudation (NSF) DEB EF-1340270 and the Climate Mitigation Initiative at the Princeton Environmental Institute, Princeton University. SL acknowledges financial support from the China Scholarship Council (CSC). VRD acknowledges funding from Ramón y Cajal fellowship (RYC-2012-10970). BTW was supported by the Next-Generation Ecosystem Experiments (NGEE)–Tropics project, funded by the Office of Biological and Environmental Research, within the U.S. Department of Energy Office of Science. DJC acknowledges funding from the National Science Centre, Poland (NN309 713340). WRLA was supported in part by NSF DEB 1714972.

Publications
Anderegg, W. R. L. et al. "Plant water potential improves prediction of empirical stomatal models." PLOS ONE 12, e0185481 (2017).[DOI:10.1371/journal.pone.0185481]

Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Next-Generation Ecosystem Experiments (NGEE)

Division: SC-33.1 Earth and Environmental Sciences Division, BER

 

BER supports basic research and scientific user facilities to advance DOE missions in energy and environment. More about BER

Recent Highlights

Mar 23, 2021
Molecular Connections from Plants to Fungi to Ants
Lipids transfer energy and serve as an inter-kingdom communication tool in leaf-cutter ants&rsqu [more...]

Mar 19, 2021
Microbes Use Ancient Metabolism to Cycle Phosphorus
Microbial cycling of phosphorus through reduction-oxidation reactions is older and more widespre [more...]

Feb 22, 2021
Warming Soil Means Stronger Microbe Networks
Soil warming leads to more complex, larger, and more connected networks of microbes in those soi [more...]

Jan 27, 2021
Labeling the Thale Cress Metabolites
New data pipeline identifies metabolites following heavy isotope labeling.

Analysis [more...]

Aug 31, 2020
Novel Bacterial Clade Reveals Origin of Form I Rubisco
Objectives

  • All plant biomass is sourced from the carbon-fixing enzyme Rub [more...]

List all highlights (possible long download time)