Diversity in stomatal function is integral to modelling plant carbon and water fluxes

  • Nature Ecology & Evolution 112921298 (2017)
  • doi:10.1038/s41559-017-0238-z
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Stomatal pores on leaf surfaces respond to environmental and physiological signals to regulate leaf gas exchange. Mathematical models can predict stomatal conductance (gs), with one parameter (m or gl) reflecting the sensitivity of gs to the photosynthetic rate (A), atmospheric carbon dioxide concentration and atmospheric humidity, and a second parameter (g0) representing the minimum gs. Such models are solved iteratively with a photosynthesis model to form the core of many models of crop or ecosystem carbon and water fluxes. For three decades, gs models have frequently been used assuming fixed parameter values for m or g1 and g0 across species and major plant functional types. This study of temperate tree species reveals significant interspecific variation in stomatal function. Applying species-specific parameterizations substantially reduced error in model predictions of gs by 34 to 64% and A by 52 to 60% and resulted in significant correlation between modelled and measured values. This work challenges the long-held assumption of fixed parameter values and, in doing so, suggests an approach for reducing modelling error across a wide range of ecological and agricultural applications.

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Support for this project was provided by the Illinois Biomathematics Program via a grant from National Science Foundation (Division of Undergraduate Education, Award # 1129198) and the Energy Biosciences Institute. The authors thank G. Kling and the Energy Biosciences Institute Bioenergy Farm for access to the plant material used in this study, M. Dietze for assistance with model assembly, D. Rosenthal for technical support with photosynthetic gas exchange, E. Ainsworth for comments on the draft manuscript and M. de Kauwe for valuable reviews of the original manuscript.

Author information

Author notes

    • Dan Wang

    Present address: International Center of Ecology, Meteorology and Environment, Nanjing University of Information, Science and Technology, Nanjing Shi, Jiangsu, China


  1. Department of Plant Biology and Energy Biosciences Institute and Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    • Kevin J. Wolz
    • , Timothy M. Wertin
    • , Dan Wang
    •  & Andrew D. B. Leakey
  2. Program in Ecology, Evolution and Conservation Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    • Kevin J. Wolz
  3. Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    • Mark Abordo


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A.D.B.L. and K.J.W. designed the experiment. K.J.W., T.M.W., M.A. and D.W. collected the data. K.J.W. performed the modelling. K.J.W., T.M.W. and A.D.B.L. performed the statistical analyses. A.D.B.L. and K.J.W. wrote the paper with significant revisions from T.M.W. All authors discussed the results and commented on the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Andrew D. B. Leakey.

Electronic supplementary material

  1. Supplementary Information

    Supplementary Tables 1–3; Supplementary Figures 1–10

  2. Supplementary Data 1

    In situ gas exchange data

  3. Supplementary Data 2

    Lab gas exchange data

  4. Supplementary Data 3

    In situ model fits

  5. Supplementary Data 4

    Model inputs and outputs

  6. Supplementary Data 5

    Coupled model code