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 over-predict 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. A team from the University of Utah, in conjunction with NGEE-Tropics 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 over predicted 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 PM)
Daniel Stover
SC-23.1
Daniel.Stover@science.doe.gov

Dorothy Koch
SC-23.1
Dorothy.Koch@science.doe.gov

(PI Contact)
William R. L. Anderegg
University of Utah
anderegg@utah.edu

Funding
Funding for this research was provided by 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-Tropics, funded by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research. 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., A. Wolf, A. Arango-Velez, B. Choat, D.J. Chmura, S. Jansen, T. Kolb, S. Li, F. Meinzer, P. Pita, V.R. de Dios, J.S. Sperry, B.T. Wolfe, S. Pacala. “Plant water potential improves prediction of empirical stomatal models.” PLoS ONE 12(10), 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-23.1 Climate 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

Aug 24, 2019
New Approach for Studying How Microbes Influence Their Environment
A diverse group of scientists suggests a common framework and targeting of known microbial processes [more...]

Aug 08, 2019
Nutrient-Hungry Peatland Microbes Reduce Carbon Loss Under Warmer Conditions
Enzyme production in peatlands reduces carbon lost to respiration under future high temperatures. [more...]

Aug 05, 2019
Amazon Forest Response to CO2 Fertilization Dependent on Plant Phosphorus Acquisition
AmazonFACE Model Intercomparison. The Science Plant growth is dependent on the availabi [more...]

Jul 29, 2019
A Slippery Slope: Soil Carbon Destabilization
Carbon gain or loss depends on the balance between competing biological, chemical, and physical reac [more...]

Jul 15, 2019
Field Evaluation of Gas Analyzers for Measuring Ecosystem Fluxes
How gas analyzer type and correction method impact measured fluxes. The Science A side- [more...]

List all highlights (possible long download time)