The optimization of photosynthetic gain and hydraulic cost to predict stomatal responses

 

 

Predicting stomatal responses to the environment from the optimization of photosynthetic gain and hydraulic cost

by Sperry J. S., Venturas M. D., Anderegg W. R. I., Mencuccini M., Mackay D. S., Wang Y., Love D. M. (2016)

University of Utah, Salt Lake City, UT, USA

John S. Sperry,

Martin D. Venturas,

William R.L. Anderegg,

Maurizio Mencuccini,

D. Scott Mackay,

Yujie Wang,

David M. Love

in Plant, Cell @ Environment – DOI: 10.1111/pce.12852 – Accepted, unedited articles published online

http://onlinelibrary.wiley.com/doi/10.1111/pce.12852/abstract

Abstract

Stomatal regulation presumably evolved to optimize CO2 for H2O exchange in response to changing conditions. If the optimization criterion can be readily measured or calculated, then stomatal responses can be efficiently modeled without recourse to empirical models or underlying mechanism. Previous efforts have been challenged by the lack of a transparent index for the cost of losing water. Yet it is accepted that stomata control water loss to avoid excessive loss of hydraulic conductance from cavitation and soil drying.

Proximity to hydraulic failure and desiccation can represent the cost of water loss. If at any given instant the stomatal aperture adjusts to maximize the instantaneous difference between photosynthetic gain and hydraulic cost, then a model can predict the trajectory of stomatal responses to changes in environment across time.

Results of this optimization model are consistent with the widely used Ball-Berry-Leuning empirical model (r2 > 0.99) across a wide range of vapor pressure deficits and ambient CO2 concentrations for wet soil.

The advantage of the optimization approach is the absence of empirical coefficients, applicability to dry as well as wet soil, and prediction of plant hydraulic status along with gas exchange.

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Published by

Willem Van Cotthem

Honorary Professor of Botany, University of Ghent (Belgium). Scientific Consultant for Desertification and Sustainable Development.

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