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Abstract 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. 

Abstract PremisePrevious studies have suggested a trade‐off between trichome density (D_t) and stomatal density (D_s) due to shared cell precursors. We clarified how, when, and why this developmental trade‐off may be overcome across species. MethodsWe derived equations to determine the developmental basis forD_tandD_sin trichome and stomatal indices (i_tandi_s) and the sizes of epidermal pavement cells (e), trichome bases (t), and stomata (s) and quantified the importance of these determinants ofD_tandD_sfor 78 California species. We compiled 17 previous studies ofD_t–D_srelationships to determine the commonness ofD_t–D_sassociations. We modeled the consequences of differentD_t–D_sassociations for plant carbon balance. ResultsOur analyses showed that higherD_twas determined by higheri_tand lowere, and higherD_sby higheri_sand lowere. Across California species, positiveD_t–D_scoordination arose due toi_t–i_scoordination and impacts of the variation ine. AD_t–D_strade‐off was found in only 30% of studies. Heuristic modeling showed that species sets would have the highest carbon balance with a positive or negative relationship or decoupling ofD_tandD_s, depending on environmental conditions. ConclusionsShared precursor cells of trichomes and stomata do not limit higher numbers of both cell types or drive a generalD_t–D_strade‐off across species. This developmental flexibility across diverse species enables differentD_t–D_sassociations according to environmental pressures. Developmental trait analysis can clarify how contrasting trait associations would arise within and across species. 

Abstract Background Remote sensing instruments enable high-throughput phenotyping of plant traits and stress resilience across scale. Spatial (handheld devices, towers, drones, airborne, and satellites) and temporal (continuous or intermittent) tradeoffs can enable or constrain plant science applications. Here, we describe the technical details of TSWIFT (Tower Spectrometer on Wheels for Investigating Frequent Timeseries), a mobile tower-based hyperspectral remote sensing system for continuous monitoring of spectral reflectance across visible-near infrared regions with the capacity to resolve solar-induced fluorescence (SIF). Results We demonstrate potential applications for monitoring short-term (diurnal) and long-term (seasonal) variation of vegetation for high-throughput phenotyping applications. We deployed TSWIFT in a field experiment of 300 common bean genotypes in two treatments: control (irrigated) and drought (terminal drought). We evaluated the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), and SIF, as well as the coefficient of variation (CV) across the visible-near infrared spectral range (400 to 900 nm). NDVI tracked structural variation early in the growing season, following initial plant growth and development. PRI and SIF were more dynamic, exhibiting variation diurnally and seasonally, enabling quantification of genotypic variation in physiological response to drought conditions. Beyond vegetation indices, CV of hyperspectral reflectance showed the most variability across genotypes, treatment, and time in the visible and red-edge spectral regions. Conclusions TSWIFT enables continuous and automated monitoring of hyperspectral reflectance for assessing variation in plant structure and function at high spatial and temporal resolutions for high-throughput phenotyping. Mobile, tower-based systems like this can provide short- and long-term datasets to assess genotypic and/or management responses to the environment, and ultimately enable the spectral prediction of resource-use efficiency, stress resilience, productivity and yield. 

Abstract Changes in leaf temperature are known to drive stomatal responses, because the leaf‐to‐air water vapour gradient (Δw) increases with temperature if ambient vapour pressure is held constant, and stomata respond to changes in Δw. However, the direct response of stomata to temperature (DRST; the response when Δwis held constant by adjusting ambient humidity) has been examined far less extensively. Though the meagre available data suggest the response is usually positive, results differ widely and defy broad generalisation. As a result, little is known about the DRST. This review discusses the current state of knowledge about the DRST, including numerous hypothesised biophysical mechanisms, potential implications of the response for plant adaptation, and possible impacts of the DRST on plant‐atmosphere carbon and water exchange in a changing climate. 

Proximal remote sensing offers a powerful tool for high-throughput phenotyping of plants for assessing stress response. Bean plants, an important legume for human consumption, are often grown in regions with limited rainfall and irrigation and are therefore bred to further enhance drought tolerance. We assessed physiological (stomatal conductance and predawn and midday leaf water potential) and ground- and tower-based hyperspectral remote sensing (400 to 2,400 nm and 400 to 900 nm, respectively) measurements to evaluate drought response in 12 common bean and 4 tepary bean genotypes across 3 field campaigns (1 predrought and 2 post-drought). Hyperspectral data in partial least squares regression models predicted these physiological traits ( R 2 = 0.20 to 0.55; root mean square percent error 16% to 31%). Furthermore, ground-based partial least squares regression models successfully ranked genotypic drought responses similar to the physiologically based ranks. This study demonstrates applications of high-resolution hyperspectral remote sensing for predicting plant traits and phenotyping drought response across genotypes for vegetation monitoring and breeding population screening. 

Abstract Sap velocity measurements are useful in fields ranging from plant water relations to hydrology at a variety of scales. Techniques based on pulses of heat are among the most common methods to measure sap velocity, but most lack ability to measure velocities across a wide range, including very high, very low and negative velocities (reverse flow). We propose a new method, the double-ratio method (DRM), which is robust across an unprecedented range of sap velocities and provides real-time estimates of the thermal diffusivity of wood. The DRM employs one temperature sensor upstream (proximal) and two sensors downstream (distal) to the source of heat. This facilitates several theoretical, heat-based approaches to quantifying sap velocity. We tested the DRM using whole-tree lysimetry in Eucalyptus cypellocarpa L.A.S. Johnson and found strong agreement across a wide range of velocities.