Optimization theory explains nighttime stomatal responses

Pinpointing the causal influences of stomatal anatomy and behavior on minimum, operational, and maximum leaf surface conductance

Leaf surface conductance to water vapor and CO2 across the epidermis (gleaf) strongly determines the rates of gas exchange. Thus, clarifying the drivers of gleaf has important implications for resolving the mechanisms of photosynthetic productivity and leaf and plant responses and tolerance to drought. It is well recognized that gleaf is a function of the conductances of the stomata (gs) and of the epidermis + cuticle (gec). Yet, controversies have arisen around the relative roles of stomatal density (d) and size (s), fractional stomatal opening (α; aperture relative to maximum), and gec in determining gleaf. Resolving the importance of these drivers is critical across the range of leaf surface conductances, from strong stomatal closure under drought (gleaf,min), to typical opening for photosynthesis (gleaf,op), to maximum achievable opening (gleaf,max). We derived equations and analyzed a compiled database of published and measured data for approximately 200 species and genotypes. On average, within and across species, higher gleaf,min was determined 10 times more strongly by α and gec than by d and negligibly by s; higher gleaf,op was determined approximately equally by α (47%) and by stomatal anatomy (45% by d and 8% by s), and negligibly by gec; and higher gleaf,max was determined entirely by d. These findings clarify how diversity in stomatal functioning arises from multiple structural and physiological causes with importance shifting with context. The rising importance of d relative to α, from gleaf,min to gleaf,op, enables even species with low gleaf,min, which can retain leaves through drought, to possess high d and thereby achieve rapid gas exchange in periods of high water availability.

Measured leaf dark respiratory CO2 -release is not controlled by stomatal conductance

Leaf dark respiratory CO2 -release (RD ) is, according to some literature, dependent on the rate of leaf transpiration. If this is true, then at a given vapor pressure deficit, the leaf stomatal conductance (gs ) will be expected to be a controlling factor of measured RD at any given time. We artificially lowered leaf gs by applying abscisic acid (ABA). Although leaf RD generally covaried temporally with gs , artificially lowering gs by applying ABA does not affect the measured leaf RD . These results indicate that observed diel fluctuations in gs are not directly influencing the measured leaf RD , thereby simplifying both future studies and the interpretation of past studies of the underlying environmental- and physiological drivers of temporal variation in leaf RD .

A wearable and capacitive sensor for leaf moisture status monitoring

The real-time and precise monitoring of plant physiological information, such as leaf capacitance, is important in agricultural production. However, current approaches for leaf capacitance monitoring are easy to cause damage to plants, which would decrease the accuracy of monitoring. In this study, we proposed the wearable electrodes for real-time monitoring of leaf capacitance. Gold nanoparticles were magnetron sputterred on polyethylene terephthalate (PET) membrane to form the wearable Au@PET electrodes. Due to their excellent flexibility, the electrodes showed good stability in both conductivity and capacitance sensing. The electrodes could be conformally attached to the leaf surface to form leaf capacitance sensor. It was found that capacitance value was positively correlated with leaf moisture content. Additionally, leaf capacitance showed higher value at night than daytime, with an extent of 12.02% and the results obtained from Au@PET electrodes were similar to the ones from traditional rigid electrodes. Besides, the growth and physiological parameters of Epipremnum aureum were not significantly affected during capacitance monitoring by Au@PET electrodes. Such results demonstrated the potential of wearable electrodes for real-time and precise monitoring of plant physiological information in the future.

Dark respiration explains nocturnal stomatal conductance in rice regardless of drought and nutrient stress

The ecological mechanism underlying nocturnal stomatal conductance (gsn ) in C3 and C4 plants remains elusive. In this study, we proposed a 'coordinated leaf trait' hypothesis to explain gsn in rice plants. We conducted an open-field experiment by applying drought, nutrient stress and the combined drought-nutrient stress. We found that gsn was neither strongly reduced by drought nor consistently increased by nutrient stress. With the aforementioned multiple abiotic stressors considered as random effects, gsn exhibited a strong positive correlation with dark respiration (Rn ). Notably, gsn primed early morning (5:00-7:00) photosynthesis through faster stomatal response time. This photosynthesis priming effect diminished after mid-morning (9:00). Leaves were cooled by gsn -derived transpiration. However, our results clearly suggest that evaporative cooling did not reduce dark respiration cost. Our results indicate that gsn is more closely related to carbon respiration and assimilation than water and nutrient availability, and that dark respiration can explain considerable variation of gsn .

Dynamically optimizing stomatal conductance for maximum turgor-driven growth over diel and seasonal cycles

Stomata have recently been theorized to have evolved strategies that maximize turgor-driven growth over plants' lifetimes, finding support through steady-state solutions in which gas exchange, carbohydrate storage and growth have all reached equilibrium. However, plants do not operate near steady state as plant responses and environmental forcings vary diurnally and seasonally. It remains unclear how gas exchange, carbohydrate storage and growth should be dynamically coordinated for stomata to maximize growth. We simulated the gas exchange, carbohydrate storage and growth that dynamically maximize growth diurnally and annually. Additionally, we test whether the growth-optimization hypothesis explains nocturnal stomatal opening, particularly through diel changes in temperature, carbohydrate storage and demand. Year-long dynamic simulations captured realistic diurnal and seasonal patterns in gas exchange as well as realistic seasonal patterns in carbohydrate storage and growth, improving upon unrealistic carbohydrate responses in steady-state simulations. Diurnal patterns of carbohydrate storage and growth in day-long simulations were hindered by faulty modelling assumptions of cyclic carbohydrate storage over an individual day and synchronization of the expansive and hardening phases of growth, respectively. The growth-optimization hypothesis cannot currently explain nocturnal stomatal opening unless employing corrective 'fitness factors' or reframing the theory in a probabilistic manner, in which stomata adopt an inaccurate statistical 'memory' of night-time temperature. The growth-optimization hypothesis suggests that diurnal and seasonal patterns of stomatal conductance are driven by a dynamic carbon-use strategy that seeks to maintain homeostasis of carbohydrate reserves.

Night-time warming in the field reduces nocturnal stomatal conductance and grain yield but does not alter daytime physiological responses

Global nocturnal temperatures are rising more rapidly than daytime temperatures and have a large effect on crop productivity. In particular, stomatal conductance at night (gsn ) is surprisingly poorly understood and has not been investigated despite constituting a significant proportion of overall canopy water loss. Here, we present the results of 3 yr of field data using 12 spring Triticum aestivum genotypes which were grown in NW Mexico and subjected to an artificial increase in night-time temperatures of 2°C. Under nocturnal heating, grain yields decreased (1.9% per 1°C) without significant changes in daytime leaf-level physiological responses. Under warmer nights, there were significant differences in the magnitude and decrease in gsn , values of which were between 9 and 33% of daytime rates while respiration appeared to acclimate to higher temperatures. Decreases in grain yield were genotype-specific; genotypes categorised as heat tolerant demonstrated some of the greatest declines in yield in response to warmer nights. We conclude the essential components of nocturnal heat tolerance in wheat are uncoupled from resilience to daytime temperatures, raising fundamental questions for physiological breeding. Furthermore, this study discusses key physiological traits such as pollen viability, root depth and irrigation type may also play a role in genotype-specific nocturnal heat tolerance.

Plant water use theory should incorporate hypotheses about extreme environments, population ecology, and community ecology

Plant water use theory has largely been developed within a plant-performance paradigm that conceptualizes water use in terms of value for carbon gain and that sits within a neoclassical economic framework. This theory works very well in many contexts but does not consider other values of water to plants that could impact their fitness. Here, we survey a range of alternative hypotheses for drivers of water use and stomatal regulation. These hypotheses are organized around relevance to extreme environments, population ecology, and community ecology. Most of these hypotheses are not yet empirically tested and some are controversial (e.g. requiring more agency and behavior than is commonly believed possible for plants). Some hypotheses, especially those focused around using water to avoid thermal stress, using water to promote reproduction instead of growth, and using water to hoard it, may be useful to incorporate into theory or to implement in Earth System Models.

Nocturnal pollutant uptake contributes significantly to the total stomatal uptake of Mangifera indica

DO₃SE (Deposition of Ozone for Stomatal Exchange), is a dry deposition model, designed to assess tropospheric ozone risk to vegetation, and is based on two alternative algorithms to estimate stomatal conductance: multiplicative and photosynthetic. The multiplicative model has been argued to perform better for leaf-level and regional-level application. In this study, we demonstrate that the photosynthetic model is superior to the multiplicative model even for leaf-level studies using measurements performed on Mangifera indica. We find that the multiplicative model overestimates the daytime stomatal conductance, when compared with measured stomatal conductance and prescribes zero conductance at night while measurements show an average conductance of 100 mmol(H₂O)m^-2s^-1 between 9 p.m. and 4 a.m. The daytime overestimation of the multiplicative model can be significantly reduced when the model is modified to include a response function for ozone-induced stomatal closure. However, nighttime pollutant uptake fluxes can only be accurately assessed with the photosynthetic model which includes the stomatal opening at night during respiration and is capable of reproducing the measured nighttime stomatal conductance. At our site, the nocturnal flux contributes 64%, 39%, 46%, and 88% of the total for NO₂ uptake in winter, summer, monsoon, and post-monsoon, respectively. For SO_2, nocturnal uptake amounts to 35%, 28%, 28%, and 44% in winter, summer, monsoon, and post-monsoon, respectively while for ozone the nighttime uptake contributes 30%, 17%, 18%, and 29% of the total stomatal uptake in winter, summer, monsoon, and post-monsoon respectively.

GriddingMachine, a database and software for Earth system modeling at global and regional scales

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

Nocturnal stomatal conductance in wheat is growth-stage specific and shows genotypic variation

Nocturnal stomatal conductance (g_sn ) represents a significant source of water loss, with implications for metabolism, thermal regulation and water-use efficiency. With increasing nocturnal temperatures due to climate change, it is vital to identify and understand variation in the magnitude and responses of g_sn in major crops. We assessed interspecific variation in g_sn and daytime stomatal conductance (g_s ) in a wild relative and modern spring wheat genotype. To investigate intraspecific variation, we grew six modern wheat genotypes and two landraces under well watered, simulated field conditions. For the diurnal data, higher g_sn in the wild relative was associated with significantly lower nocturnal respiration and higher daytime CO₂ assimilation while both species exhibited declines in g_sn post-dusk and pre-dawn. Lifetime g_sn achieved rates of 5.7-18.9% of g_s . Magnitude of g_sn was genotype specific 'and positively correlated with g_s . g_sn and g_s were significantly higher on the adaxial surface. No relationship was determined between harvest characteristics, stomatal morphology and g_sn , while cuticular conductance was genotype specific. Finally, for the majority of genotypes, g_sn declined with age. Here we present the discovery that variation in g_sn occurs across developmental, morphological and temporal scales in nonstressed wheat, presenting opportunities for exploiting intrinsic variation under heat or water stressed conditions.

Nighttime transpirational cooling enabled by circadian regulation of stomatal conductance is related to stomatal anatomy and leaf morphology in rice

Rice genotypes with larger stomata maintain higher nocturnal stomatal conductance, thus having lower nocturnal leaf temperature via transpirational cooling. Incomplete night stomatal closure has been widely observed, but the mechanisms and functions of nocturnal stomatal conductance (g_s,n) are not fully understood. Stomatal anatomy, leaf morphology, g_s,n and nocturnal leaf temperature (T_leaf,n) were measured in 30 Oryza genotypes. Nocturnal leaf conductance (g_n) showed a significant circadian rhythm; it gradually increased by 58% from 20:30 to 04:30. Contrary to cuticular conductance (g_cut), g_s,n was highly correlated with g_n. Moreover, g_s,n accounted for 76% of g_n. T_leaf,n was significantly lower than the air temperature, and was negatively correlated with both g_s,n and nocturnal transpiration rate (E_n). g_s,n was positively correlated with stomatal size, intervein distance between major veins (IVD_major), leaf thickness (LT), individual leaf area (LA), and leaf width (LW). It was also found negatively correlated with stomatal density. Reversely, T_leaf,n was negatively correlated with stomatal size, IVD_major, intervein distance between minor veins, LA and LW. T_leaf,n presented a positive correlation with stomatal density. This study highlights the importance of stomatal anatomy and leaf morphology on regulating g_s,n and T_leaf,n. The underlying mechanisms to the determinants of g_s,n and the physiological and ecological functions of the T_leaf,n regulation on rice growth and production were carefully discussed.