Plant water potential improves prediction of empirical stomatal models

Abstract

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

The response of stomatal conductance to seasonal drought in tropical forests

“…Several recent studies have suggested that Ψ leaf should be incorporated into models of g s (e.g. Anderegg et al, ; Drake et al, ; Sperry et al, ; Venturas et al, ; Zhou et al, ). However, in our study the data do not support this argument, at least for the tropical evergreen canopy trees analyzed here (Figures and ; Figure S5).…”

“…This can arise either from the shorter timescale (e.g. diurnal) coordinated variation between leaf water potential and D (Anderegg et al, ), from the increasing soil moisture stress that can induce the associated change in plant water potential which down‐regulates g s and thus the slope parameters (e.g. Drake et al, ; Heroult et al, ; Zhou et al, ), or there is coordinated acclimation of the slope parameter with seasonal variation in soil moisture and plant water potential (e.g.…”

“…Koepke & Kolb, ; Xu & Baldocchi, ). Regardless of the reasons, the inclusion of a plant or leaf water potential variable with the original g s formulations has recently been increasingly advocated as a way to improve prediction of g s (Anderegg et al, ; Drake et al, ; Zhou et al, ). Despite the recommendation of these previous studies, it remains unclear whether these results are representative of wider natural plant communities, and importantly, systems such as the tropics where tall canopy evergreen trees have evolved root systems to adapt to seasonal variability in soil moisture content (Giardina et al, ; Meinzer et al, ).…”

Land–atmospheric feedbacks during droughts and heatwaves: state of the science and current challenges

“…As such, it is still unlikely that state‐of‐the‐art climate models accurately represent the potential of droughts and heatwaves to self‐intensify via land feedbacks. However, there is significant progress in model representation of the transpiration response to stress conditions in land surface schemes; a more evolved coupling of transpiration to photosynthesis involving the explicit characterization of plant hydraulics is slowly becoming a reality . Since these processes affect the temporal and spatial response of land evaporation during droughts and heatwaves, their improved representation in land surface schemes is expected to have an impact on the projected duration and intensity of the events.…”

A stomatal control model based on optimization of carbon gain versus hydraulic risk predicts aspen sapling responses to drought

“…Mechanistic models provide insight, but are incomplete and can be difficult to parameterize (Buckley & Mott, ). Most canopy‐scale models (Tuzet et al ., ; Powell et al ., ; Anderegg et al ., ; Drake et al ., ) resort to empirical representations of stomatal conductance ( G ):where A is the rate of photosynthesis, C is CO 2 concentration either in the leaf or air, WS is a measure of soil or plant water status, and c 1 , c 2 , etc., are empirically determined coefficients that are usually constant for a particular species or functional type. At each time step, submodels based on photosynthetic biochemistry, diffusion and hydraulics of plant and/or soil provide the array of physiologically possible choices for G , A , C and WS.…”