Hydraulic theory predicts stomatal responses to climatic water deficits

Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits

by Sperry J. S., Wang Y., Wolfe B. T., Mackay D. S., Anderegg W. R. L., McDowell N. G., Pockman W. T. (2016)

John Sperry, Yujie Wang, Brett Wolfe, D. Scott Mackay, William R L Anderegg, Nate McDowell, William Pockman,

Sperry JS1Wang Y2Wolfe BT3Mackay DS4Anderegg WR2McDowell NG5Pockman WT6.

1 Department of Biology, University of Utah, Salt Lake City, UT, 84112, USA.

2 Department of Biology, University of Utah, Salt Lake City, UT, 84112, USA.

3 Smithsonian Tropical Research Institute, PO Box 0843-03092, Balboa, Panama.

4 Department of Geography, State University of New York, Buffalo, NY, 14260, USA.

5 Earth and Environmental Sciences Division, Los Alamos National Lab, Los Alamos, NM, 87545, USA.

6 Biology Department, University of New Mexico, Albuquerque, NM, 87131, USA.


In New Phytol. 212: 577–589 – DOI: 10.1111/nph.14059



Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere.

We evaluate a ‘supply-demand’ theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying.

The theory was implemented in a trait-based soil-plant-atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (Pcanopy ) from soil water potential (Psoil ) and vapor pressure deficit (D). Modeled responses to D and Psoil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients.

Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and Pcanopy across nine data sets from seasonally dry tropical forest and piñon-juniper woodland with < 26% mean error.

Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root-stem-leaf continuum will simplify parameterization

Stomata and models to develop a multi-scale assessment of the impact of changing c(a) on CO2 uptake and water use



Sensitivity of plants to changing atmospheric CO2concentration: from the geological past to the next century

by Franks P. J., Adams M. A., Amthor J. S., Barbour M. M., Berry J. A., Ellsworth D. S., Farquhar G. D., Ghannoum O., Lloyd J., McDowell N., Norby R. J., Tissue D. T., von Caemmerer S. (2013)


Faculty of Agriculture and Environment, University of Sydney, Sydney, NSW, Australia


in New Phytol. 197(4): 1077-1094 – https://doi.org/10.1111/nph.12104 – 

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The rate of CO(2) assimilation by plants is directly influenced by the concentration of CO(2) in the atmosphere, c(a). As an environmental variable, c(a) also has a unique global and historic significance. Although relatively stable and uniform in the short term, global c(a) has varied substantially on the timescale of thousands to millions of years, and currently is increasing at seemingly an unprecedented rate. This may exert profound impacts on both climate and plant function.

Here we utilise extensive datasets and models to develop an integrated, multi-scale assessment of the impact of changing c(a) on plant carbon dioxide uptake and water use.

We find that, overall, the sensitivity of plants to rising or falling c(a) is qualitatively similar across all scales considered. It is characterised by an adaptive feedback response that tends to maintain 1 – c(i)/c(a), the relative gradient for CO(2) diffusion into the leaf, relatively constant.

This is achieved through predictable adjustments to stomatal anatomy and chloroplast biochemistry. Importantly, the long-term response to changing c(a) can be described by simple equations rooted in the formulation of more commonly studied short-term responses.