The ecohydrological context of drought and classification of plant responses.

Many recent studies on drought-induced vegetation mortality have explored how plant functional traits, and classifications of such traits along axes of, for example, isohydry-anisohydry, might contribute to predicting drought survival and recovery. As these studies proliferate, the consistency and predictive value of such classifications need to be carefully examined. Here, we outline the basis for a systematic classification of plant drought responses that accounts for both environmental conditions and functional traits. We use non-dimensional analysis to integrate plant traits and metrics of environmental variation into groups that can be associated with alternative drought stress pathways (hydraulic failure and carbon limitation), and demonstrate that these groupings predict physiological drought outcomes using both synthetic and measured data. In doing so, we aim to untangle some confounding effects of environment and trait variations that undermine current classification schemes, advocate for more careful treatment of the environmental context within which plants experience and respond to drought, and outline a pathway towards a general classification of drought vulnerability.

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

Empirical models of plant drought responses rely on parameters that are difficult to specify a priori. We test a trait- and process-based model to predict environmental responses from an optimization of carbon gain vs hydraulic risk. We applied four drought treatments to aspen (Populus tremuloides) saplings in a research garden. First we tested the optimization algorithm by using predawn xylem pressure as an input. We then tested the full model which calculates root-zone water budget and xylem pressure hourly throughout the growing season. The optimization algorithm performed well when run from measured predawn pressures. The per cent mean absolute error (MAE) averaged 27.7% for midday xylem pressure, transpiration, net assimilation, leaf temperature, sapflow, diffusive conductance and soil-canopy hydraulic conductance. Average MAE was 31.2% for the same observations when the full model was run from irrigation and rain data. Saplings that died were projected to exceed 85% loss in soil-canopy hydraulic conductance, whereas surviving plants never reached this threshold. The model fit was equivalent to that of an empirical model, but with the advantage that all inputs are specific traits. Prediction is empowered because knowing these traits allows knowing the response to climatic stress.

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

Stomatal regulation presumably evolved to optimize CO2 for H2 O exchange in response to changing conditions. If the optimization criterion can be readily measured or calculated, then stomatal responses can be efficiently modelled 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 vapour 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.

Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits.

Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere. We evaluate a 'supply-demand' theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying. The theory was implemented in a trait-based soil-plant-atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (Pcanopy ) from soil water potential (Psoil ) and vapor pressure deficit (D). Modeled responses to D and Psoil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients. Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and Pcanopy across nine data sets from seasonally dry tropical forest and piñon-juniper woodland with < 26% mean error. Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root-stem-leaf continuum will simplify parameterization.

What plant hydraulics can tell us about responses to climate-change droughts.

Climate change exposes vegetation to unusual drought, causing declines in productivity and increased mortality. Drought responses are hard to anticipate because canopy transpiration and diffusive conductance (G) respond to drying soil and vapor pressure deficit (D) in complex ways. A growing database of hydraulic traits, combined with a parsimonious theory of tree water transport and its regulation, may improve predictions of at-risk vegetation. The theory uses the physics of flow through soil and xylem to quantify how canopy water supply declines with drought and ceases by hydraulic failure. This transpiration 'supply function' is used to predict a water 'loss function' by assuming that stomatal regulation exploits transport capacity while avoiding failure. Supply-loss theory incorporates root distribution, hydraulic redistribution, cavitation vulnerability, and cavitation reversal. The theory efficiently defines stomatal responses to D, drying soil, and hydraulic vulnerability. Driving the theory with climate predicts drought-induced loss of plant hydraulic conductance (k), canopy G, carbon assimilation, and productivity. Data lead to the 'chronic stress hypothesis' wherein > 60% loss of k increases mortality by multiple mechanisms. Supply-loss theory predicts the climatic conditions that push vegetation over this risk threshold. The theory's simplicity and predictive power encourage testing and application in large-scale modeling.