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Summary: Stomatal optimization models can improve estimates of water and carbon fluxes with relatively low complexity, yet there is no consensus on which formulations are most appropriate for ecosystem‐scale applications. We implemented three existing analytical equations for stomatal conductance, based on different water penalty functions, in a big‐leaf comparison framework, and determined which optimization principles were most consistent with flux tower observations from different biomes.We used information theory to dissect controls of soil water supply and atmospheric demand on evapotranspiration in wet to dry conditions and to quantify missing or inadequate information in model variants. We ranked stomatal optimization principles based on parameter uncertainty, parsimony, predictive accuracy, and functional accuracy of the interactions between soil moisture, vapor pressure deficit, and evapotranspiration.Performance was high for all model variants. Water penalty functions with explicit representation of plant hydraulics did not substantially improve predictive or functional accuracy of ecosystem‐scale evapotranspiration estimates, and parameterizations were more uncertain, despite having physiological underpinnings at the plant level.Stomatal optimization based on water use efficiency thus provided more information about ecosystem‐scale evapotranspiration compared to those based on xylem vulnerability and proved more useful in improving ecosystem‐scale models with less complexity. [ABSTRACT FROM AUTHOR]

Despite the appeal of the iso/anisohydric framework for classifying plant drought responses, recent studies have shown that such classifications can be strongly affected by a plant's environment. Here, we present measured in situ drought responses to demonstrate that apparent isohydricity can be conflated with environmental conditions that vary over space and time. In particular, we (a) use data from an oak species (Quercus douglasii) during the 2012–2015 extreme drought in California to demonstrate how temporal and spatial variability in the environment can influence plant water potential dynamics, masking the role of traits; (b) explain how these environmental variations might arise from climatic, topographic, and edaphic variability; (c) illustrate, through a "common garden" thought experiment, how existing trait‐based or response‐based isohydricity metrics can be confounded by these environmental variations, leading to Type‐1 (false positive) and Type‐2 (false negative) errors; and (d) advocate for the use of model‐based approaches for formulating alternate classification schemes. Building on recent insights from greenhouse and vineyard studies, we offer additional evidence across multiple field sites to demonstrate the importance of spatial and temporal drivers of plants' apparent isohydricity. This evidence challenges the use of isohydricity indices, per se, to characterize plant water relations at the global scale. Metrics of plant isohydricity have been used to describe plant water regulation with limited success. Here, using in situ measurements of Quercus douglasii under drought, we highlight the importance of environmental variations over space and time in influencing the apparent isohydricity of plants. [ABSTRACT FROM AUTHOR]

Background and Aims: Due to their high water use efficiency, Crassulacean acid metabolism (CAM) plants are of environmental and economic importance in the arid and semiarid regions of the world. Moreover, many CAM plants (e.g., Agave tequilana) have attractive qualities for biofuel production such as a relatively low lignin content and high amount of soluble carbohydrates. However, the current estimates of CAM productivity are based on empirical stress indices that create large uncertainties. As a first step towards a more accurate quantification of CAM productivity, this paper introduces a new model that couples both soil and atmosphere conditions to CAM photosynthesis. Methods: The new CAM model is based upon well established C photosynthesis models coupled to a nonlinear circadian rhythm oscillator for the control of the photosynthesis carbon fluxes. The leaf-level dynamics are coupled to a simple, yet realistic description of the soil-plant-atmosphere continuum, including a plant water capacitance module. Results: The resulting model reproduces the four phases of CAM photosynthes is and the evolution of their dynamics during a soil moisture drydown, as a function of soil type, plant features, and climatic conditions. Conclusion: The results help quantify the impact of soil water availability on CAM carbon assimilation and transpiration flux. [ABSTRACT FROM AUTHOR]

Summary [ABSTRACT FROM AUTHOR]

Quantification of stomatal responses to environmental variables, in particular to soil water status, is needed to model carbon and water exchange rates between plants and the atmosphere. Models based on stomatal optimality theory successfully describe leaf gas exchange under different environmental conditions, but the effects of water availability on the key optimization parameter [the marginal water use efficiency (WUE), λ = ∂ A/∂ E] has resisted complete theoretical treatment. Building on previous optimal leaf gas exchange models, we developed an analytical equation to estimate λ from gas exchange observations along gradients of soil water availability. This expression was then used in a meta-analysis of about 50 species to investigate patterns of variation in λ. Assuming that cuticular water losses are negligible λ increases under mild water stress but decreases when severe water stress limits photosynthesis. When cuticular conductance is considered, however, λ increases monotonically with increasing water stress, in agreement with previous theoretical predictions. Moreover, the shape of these response curves to soil water availability changes with plant functional type and climatic conditions. In general, λ is lower in species grown in dry climates, indicating lower marginal WUE. The proposed parameterization provides a framework to assess the responses of leaf gas exchange to changes in water availability. Moreover, the model can be extended to scale leaf-level fluxes to the canopy and ecosystem level. [ABSTRACT FROM AUTHOR]

• Non-dimensional combinations of soil, plant, and climate variables reduce the complexity of plant water use strategies. • Plant water flux control relative to demand is the non-dimensional group that primarily influences plant water use performance. • Plant water use strategies that maximize long-term mean transpiration weighted by risks of water stress match soil moisture observations. • Combining non-dimensional groups and ecohydrological optimality offers constraints to quantify and understand plant water stress responses. Plant responses to water stress influence water and carbon cycles and can lead to feedbacks on climate yet characterizing these responses at ecosystem levels remains uncertain. Quantifying ecosystem-level water use strategies is complex due to challenges of upscaling plant traits and disentangling confounding environmental factors, ultimately limiting our ability to understand and anticipate global change in ecosystem dynamics and ecohydrological fluxes. We reduce the dimensionality of this problem and quantify plant water use strategies by combining plant traits with soil and climate variables into parameter groups that synthesize key eco-physiological tradeoffs. Using a parsimonious soil water balance framework, we explore variations in plant water uptake capacity, water stress responses, and water use performance via these non-dimensional parameter groups. The group characterizing the synchronization of plant water transport and atmospheric water demand emerges as the primary axis of variation in water use strategies and interacts with the group representing plant hydraulic risk tolerance, especially in arid conditions when plant water transport is limiting. Next, we show that specific plant water use strategies maximize plant water uptake (leading to carbon gain benefits) weighted by risks of water stress (leading to higher costs of water use). A model-data comparison demonstrates that these ecohydrologically optimal parameter groups capture observed soil moisture variability in 40 ecosystems and beyond aridity, rainfall frequency is an important environmental control for plant water use strategies. The emerging parsimonious link between ecohydrological performance and non-dimensional parameters provides a tractable representation of plant water use strategies, relevant to parameterize global models while accounting for ecological and evolutionary constraints on the water cycle. [ABSTRACT FROM AUTHOR]