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Updated: Aug 17, 2025

Relating Stomatal Conductance to Leaf Functional Traits
Published on: October 12, 2015
Short-term variation in leaf-level water use efficiency in a tropical forest
Kenneth J Davidson1,2, Julien Lamour1, Alistair Rogers1
1Department of Environmental and Climate Sciences, Brookhaven National Laboratory, Building 490A, Upton, NY, 11973, USA.
Accurate stomatal conductance models are vital for predicting ecosystem responses to climate change. Diurnal variations in stomatal behavior, not leaf age, significantly improve transpiration forecasts in forest models.
Area of Science:
- Plant physiology
- Ecosystem modeling
- Global change biology
Background:
- Stomatal regulation of transpiration and CO2 assimilation is critical for forecasting terrestrial ecosystem responses to global change.
- Accurate and mechanistic model representation of stomatal conductance (gs) and assimilation is crucial for understanding forest productivity and climate relationships.
Purpose of the Study:
- To assess physiological and mechanistic controls on stomatal slope (g1) and stomatal intercept (g0) parameters.
- To improve the accuracy of modeled stomatal conductance (gs) by accounting for diurnal and measurement approach variations.
Main Methods:
- Utilized diurnal gas exchange surveys and leaf-level response curves from six tropical broadleaf evergreen tree species.
- Compared g1 estimations from ex situ response curves versus survey data.
- Analyzed variations in g0 and g1 across different phenological stages and diurnal periods.
Main Results:
- g1 estimated from ex situ response curves was 50% lower than that from survey data.
- g0 and g1 showed variation with leaf phenology, but this trend was not consistent across species.
- A diurnal trend in g1 and g0 was identified, significantly improving model projections of diurnal transpiration.
Conclusions:
- Accounting for diurnal variation in stomatal behavior and measurement approaches enhances modeled gs accuracy.
- Phenological variation in stomatal behavior is less critical than diurnal variation for improving land-surface models.
- Further research into the mechanisms driving diurnal variation in g1 is needed for comprehensive land-surface modeling.
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