Plant water potential improves prediction of empirical stomatal models

• Published in: PloS one 2017-10, Vol.12 (10), p.e0185481
• Main Authors: Anderegg, William R L, Wolf, Adam, Arango-Velez, Adriana, Choat, Brendan, Chmura, Daniel J, Jansen, Steven, Kolb, Thomas, Li, Shan, Meinzer, Frederick, Pita, Pilar, Resco de Dios, Víctor, Sperry, John S, Wolfe, Brett T, Pacala, Stephen
• Format: Article
• Language: English
• Subjects: Biology; Biology and Life Sciences; Carbon; Climate Change; Climate models; Climatic extremes; Complications and side effects; Computer simulation; Conductance; Drought; Drought conditions; Droughts; Ecology; Ecology and Environmental Sciences; Ecosystem; Ecosystem biology; ecosystem modeling; Ecosystem models; Ecosystems; Empirical models; Environment models; Environmental aspects; Environmental changes; Environmental conditions; Environmental regulations; ENVIRONMENTAL SCIENCES; flowering plants; Future climates; Hydraulics; Leaf water potential; Leaves; Moisture content; Photosynthesis - physiology; Physical Sciences; Physiological aspects; Plant diversity; Plant Leaves - physiology; Plant sciences; Plant species; Plant Stomata - physiology; Plant Transpiration - physiology; Plant water; Plant water potential; Predictions; Research and Analysis Methods; Resistance; Risk factors; Simulation; Soil water; Stomata; Stomatal conductance; Water - chemistry; Water Cycle; Water potential; water resources; Water shortages; Water stress; Water transport; Woody plants; xylem
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0185481

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.