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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.

 

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. 

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. 

A surge of papers have reported low leaf vulnerability to xylem embolism during drought. Here, we focus on the less studied, and more sensitive, outside‐xylem leaf hydraulic responses to multiple internal and external conditions. Studies of 34 species have resolved substantial vulnerability to dehydration of the outside‐xylem pathways, and studies of leaf hydraulic responses to light also implicate dynamic outside‐xylem responses. Detailed experiments suggest these dynamic responses arise at least in part from strong control of radial water movement across the vein bundle sheath. While leaf xylem vulnerability may influence leaf and plant survival during extreme drought, outside‐xylem dynamic responses are important for the control and resilience of water transport and leaf water status for gas exchange and growth.

 

Reduced stomatal conductance is a common plant response to rising atmospheric CO₂and increases water use efficiency (W). At the leaf-scale,Wdepends on water and nitrogen availability in addition to atmospheric CO₂. In hydroclimate modelsWis a key driver of rainfall, droughts, and streamflow extremes. We used global climate data to derive Aridity Indices (AI) for forests over the period 1965–2015 and synthesised those with data for nitrogen deposition andWderived from stable isotopes in tree rings. AI and atmospheric CO₂account for most of the variance inWof trees across the globe, while cumulative nitrogen deposition has a significant effect only in regions without strong legacies of atmospheric pollution. The relation of aridity andWdisplays a clear discontinuity.Wand AI are strongly related below a threshold value of AI ≈ 1 but are not related where AI > 1. Tree ring data emphasise that effective demarcation of water-limited from non-water-limited behaviour of stomata is critical to improving hydrological models that operate at regional to global scales.

 

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.