Abstract
Vegetation controls carbon and water fluxes because of the fundamental tradeoff between carbon dioxide uptake and water loss occurring when stomata are open. Quantifying the rates of this exchange typically requires either intensive gas exchange or destructive harvesting of tissues and mass spectrometry analyses. Recent developments in high-throughput methods have enhanced our capacity to empirically test plant-environmental interactions. The vast integration characterizing satellite remote sensing methods masks organ-level physiological mechanisms limiting the predictive capability of current process models. Hence, more ground truth studies are necessary to determine the amount of mechanistic information needed to improve our understanding of forest, crop, and land management. Imaging methodologies, such as thermal and chlorophyll a fluorescence, are currently used to collect information for relevant traits such as water use, growth, and stress response. We tested these techniques during progressive drought across species with different susceptibility in controlled greenhouse conditions. We chose two highly represented tree species in North America: the gymnosperm Pinus ponderosa and the angiosperm Populus tremuloides. To better explore the whole drought response parameter space, we also tested a crop (Brassica rapa) and desert shrub (Artemisia tridentata). Thermal and fluorescence images of the canopy were coupled with leaf-level measurements as we performed three tests to predict drought response using 1) leaf temperature, 2) chlorophyll a fluorescence, and 3) the combination of the two. At five days of drought, leaf temperature increased 7 and 10%, accounting for 63% and 73% of the variation in stomatal conductance for both tree species, respectively. The fluorescence signal from images decreased ~12% and ~83% in moderately and severely droughted leaves respectively, reaching zero at mortality. Leaf water status was then predicted using a Bayesian approach that incorporated measurements’ uncertainty and parsimony in the analysis of the parameters. Changes in canopy temperature provided confident predictions for the reductions of daily evapotranspiration at the onset of drought. Empirically combining thermal and fluorescence measurements improved predictions (R2 = 0.81) of midday leaf water potential compared to univariate models. Our results represent an important step towards quantifying plant water status during drought using first principles that do not require species-specific information.
Highlights
Drought is a primary contributor to the increasing levels of global plant mortality, which exacerbates the already uncertain water and food securities for the coming decades (Allen et al, 2010; Steinkamp and Hickler, 2015)
The complexity of plant response to drought is characterized by a variety of symptoms, which have been profusely analyzed in the last decades (Gorissen et al, 2004; Bréda et al, 2006; Schachtman and Goodger, 2008; Adams et al, 2009; Ruehr et al, 2009; McDowell and Sevanto, 2010; Ruan et al, 2010; Sala et al, 2010; Mcdowell, 2011; Hartmann et al, 2013; Urli et al, 2013; Sevanto et al, 2014; Salmon et al, 2015; Guadagno et al, 2017; Martínez-Vilalta and Garcia-Forner, 2017; Nolan et al, 2017)
To test our three image-based modeling approaches that predict plant water status, we first quantify the environmental variables that will be incorporated into the models
Summary
Drought is a primary contributor to the increasing levels of global plant mortality, which exacerbates the already uncertain water and food securities for the coming decades (Allen et al, 2010; Steinkamp and Hickler, 2015). The use of informative high-throughput (i.e., high number of measured plants in a short time, repeated time points, and multiple spatial locations) methods based on biophysical first principles allow for more useful predictions of plant responses to drought because they are based on mechanisms more likely to be applicable outside observations. Such approaches span from organ to ecosystem scales and can provide informative predictions in less measured environments and for divergent plant responses to stress. The magnitude of plant response varies based on endogenous stress resistance, life history, developmental stage at the stress occurrence, pre-drought conditions, and synergistic or compound stress events (e.g., antecedent stress events) (Resco et al, 2009; Camarero et al, 2011; de Vries et al, 2012; Anderegg, 2015; Guo et al, 2020)
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