# WATER-USE EFFICIENCY: ADVANCES AND CHALLENGES IN A CHANGING CLIMATE

EDITED BY : Manoj Menon, Stuart Anthony Casson, Jeffrey M. Warren, Bhabani S. Das and Michael Vincent Mickelbart PUBLISHED IN : Frontiers in Plant Science

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# WATER-USE EFFICIENCY: ADVANCES AND CHALLENGES IN A CHANGING CLIMATE

Topic Editors:

Manoj Menon, University of Sheffield, United Kingdom Stuart Anthony Casson, University of Sheffield, United Kingdom Jeffrey M. Warren, Oak Ridge National Laboratory (DOE), United States Bhabani S. Das, Indian Institute of Technology Kharagpur, India Michael Vincent Mickelbart, Purdue University, United States

Citation: Menon, M., Casson, S. A., Warren, J. M., Das, B. S., Mickelbart, M. V., eds. (2019). Water-Use Efficiency: Advances and Challenges in a Changing Climate. Lausanne: Frontiers Media. doi: 10.3389/978-2-88963-098-1

# Table of Contents

#### *04 Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015–2016 El Niño Event in the Amazon Forest*

Bruno O. Gimenez, Kolby J. Jardine, Niro Higuchi, Robinson I. Negrón-Juárez, Israel de Jesus Sampaio-Filho, Leticia O. Cobello, Clarissa G. Fontes, Todd E. Dawson, Charuleka Varadharajan, Danielle S. Christianson, Gustavo C. Spanner, Alessandro C. Araújo, Jeffrey M. Warren, Brent D. Newman, Jennifer A. Holm, Charles D. Koven, Nate G. McDowell and Jeffrey Q. Chambers

Lígia T. Bertolino, Robert S. Caine and Julie E. Gray

*44 Interactive Regimes of Reduced Irrigation and Salt Stress Depressed Tomato Water Use Efficiency at Leaf and Plant Scales by Affecting Leaf Physiology and Stem Sap Flow*

Hui Yang, Manoj K. Shukla, Xiaomin Mao, Shaozhong Kang and Taisheng Du

Donatella Danzi, Nunzio Briglia, Angelo Petrozza, Stephan Summerer, Giovanni Povero, Alberto Stivaletta, Francesco Cellini, Domenico Pignone, Domenico De Paola and Michela Janni

*88 Corrigendum: Can High Throughput Phenotyping Help Food Security in the Mediterranean Area?*

Donatella Danzi, Nunzio Briglia, Angelo Petrozza, Stephan Summerer, Giovanni Povero, Alberto Stivaletta, Francesco Cellini, Domenico Pignone, Domenico De Paola and Michela Janni

Thomas R. Sinclair

*109 Effects of 8-Year Nitrogen and Phosphorus Treatments on the Ecophysiological Traits of Two Key Species on Tibetan Plateau* Dan Wang, Tianqi Ling, Pengpeng Wang, Panpan Jing, Jiazhi Fan, Hao Wang and Yaoqi Zhang

# Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015–2016 El Niño Event in the Amazon Forest

#### Edited by:

Sebastian Leuzinger, Auckland University of Technology, New Zealand

#### Reviewed by:

Howard Scott Neufeld, Appalachian State University, United States Mario Bretfeld, University of Wyoming, United States

#### \*Correspondence:

Bruno O. Gimenez<EMAIL_ADDRESS>
†These authors have contributed equally to this work

#### Specialty section:

This article was submitted to Plant Physiology, a section of the journal Frontiers in Plant Science

Received: 29 October 2018 Accepted: 07 June 2019 Published: 28 June 2019

#### Citation:

Gimenez BO, Jardine KJ, Higuchi N, Negrón-Juárez RI, Sampaio-Filho IdJ, Cobello LO, Fontes CG, Dawson TE, Varadharajan C, Christianson DS, Spanner GC, Araújo AC, Warren JM, Newman BD, Holm JA, Koven CD, McDowell NG and Chambers JQ (2019) Species-Specific Shifts in Diurnal Sap Velocity Dynamics and Hysteretic Behavior of Ecophysiological Variables During the 2015–2016 El Niño Event in the Amazon Forest. Front. Plant Sci. 10:830. doi: 10.3389/fpls.2019.00830 Bruno O. Gimenez1 \* † , Kolby J. Jardine2† , Niro Higuchi1 , Robinson I. Negrón-Juárez2 , Israel de Jesus Sampaio-Filho1 , Leticia O. Cobello1 , Clarissa G. Fontes3 , Todd E. Dawson3 , Charuleka Varadharajan2 , Danielle S. Christianson2 , Gustavo C. Spanner1 , Alessandro C. Araújo4 , Jeffrey M. Warren5 , Brent D. Newman6 , Jennifer A. Holm2 , Charles D. Koven2 , Nate G. McDowell7 and Jeffrey Q. Chambers2,8

1 National Institute of Amazonian Research (INPA), Manaus, Brazil, 2 Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, CA, United States, 3 Department of Integrative Biology, University of California, Berkeley, Berkeley, CA, United States, 4 Embrapa Amazônia Oriental, Belém, Brazil, 5 Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, United States, 6 Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, NM, United States, 7 Pacific Northwest National Laboratory, Richland, WA, United States, 8 Department of Geography, University of California, Berkeley, Berkeley, CA, United States

Current climate change scenarios indicate warmer temperatures and the potential for more extreme droughts in the tropics, such that a mechanistic understanding of the water cycle from individual trees to landscapes is needed to adequately predict future changes in forest structure and function. In this study, we contrasted physiological responses of tropical trees during a normal dry season with the extreme dry season due to the 2015–2016 El Niño-Southern Oscillation (ENSO) event. We quantified high resolution temporal dynamics of sap velocity (Vs), stomatal conductance (gs) and leaf water potential (9L) of multiple canopy trees, and their correlations with leaf temperature (Tleaf) and environmental conditions [direct solar radiation, air temperature (Tair) and vapor pressure deficit (VPD)]. The experiment leveraged canopy access towers to measure adjacent trees at the ZF2 and Tapajós tropical forest research (near the cities of Manaus and Santarém). The temporal difference between the peak of gs (late morning) and the peak of VPD (early afternoon) is one of the major regulators of sap velocity hysteresis patterns. Sap velocity displayed species-specific diurnal hysteresis patterns reflected by changes in Tleaf. In the morning, Tleaf and sap velocity displayed a sigmoidal relationship. In the afternoon, stomatal conductance declined as Tleaf approached a daily peak, allowing 9L to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. In Manaus, hysteresis indices of the variables Tleaf−Tair and 9L−Tleaf were calculated for different species and a significant difference (p < 0.01, α = 0.05) was observed when the 2015 dry season (ENSO period) was compared with the 2017 dry season ("control scenario"). In some days during the 2015 ENSO event,

**4**

Tleaf approached 40◦C for all studied species and the differences between Tleaf and Tair reached as high at 8◦C (average difference: 1.65 ± 1.07◦C). Generally, Tleaf was higher than Tair during the middle morning to early afternoon, and lower than Tair during the early morning, late afternoon and night. Our results support the hypothesis that partial stomatal closure allows for a recovery in 9L during the afternoon period giving an observed counterclockwise hysteresis pattern between 9L and Tleaf.

Keywords: tropical forests, sap velocity, stomatal conductance, direct solar radiation, vapor pressure deficit, leaf temperature, hysteresis

#### INTRODUCTION

Evapotranspiration by terrestrial ecosystems delivers an estimated 62,000 km3 of water to the atmosphere every year, with the majority associated with plant transpiration (Jasechko et al., 2013). In the Amazon Basin, an estimated 25–50% of precipitation is recycled back to the atmosphere through forest transpiration (Eltahir and Bras, 1994; Chambers and Artaxo, 2017), with important implications for the interactions between the biosphere and atmosphere (Araújo et al., 2002; Negrón-Juárez et al., 2007). Under climate change scenarios, vegetation resilience will depend on the capacity to exploit water resources (Grossiord et al., 2017), and a mechanistic understanding of the water cycles from individual trees to landscape scales is necessary in order to predict changes in the forest structure (Chambers et al., 2014).

At the leaf level, transpiration flux is a function of vapor pressure deficit (VPD) between the leaf and the air and stomatal conductance (gs), according to Fick's law of diffusion (Costa et al., 2010). Although numerous environmental factors influence gs , net radiation, VPD and soil moisture are often considered the most important (Jarvis, 1976; Jones, 1998; Lloyd and Farquhar, 2008; Daloso et al., 2017). High leaf temperatures (Tleaf) and VPD are known to induce stomatal closure in order to minimize excessive water loss (Farquhar, 1978; Meinzer et al., 1993; Tinoco-Ojanguren and Pearcy, 1993; Oren et al., 1999b; McAdam et al., 2016; Brodribb et al., 2017). The degree of stomatal closure is a balancing act between preventing hydraulic damage while still allowing enough CO2 influx for carbon fixation to avoid carbon-starvation (Adams et al., 2017). In addition, stomatal closure limits water lost through transpiration, and thereby indirectly regulates leaf temperatures. Given that the tropics have among the narrowest seasonal temperature range of any biome globally, they may be particularly sensitive to even small increases in temperature associated with climate change (Field et al., 2014). Indeed, rising temperature and VPD are environmental factors clearly associated with increased tree mortality in the tropics (McDowell et al., 2018), with more pronounced impacts during extreme drought events in the Amazon forest, such as the El Niño-Southern Oscillation (ENSO). This reinforces the importance of having more studies that investigate the effect of these variables (temperature and VPD) in the tropics, especially focusing on comparisons between two distinct periods, such as normal years (control scenario) and years with ENSO. This kind of approach can be considered as a "natural experiment" and allow to expand our understanding of the coupling of tree water use (and concurrent carbon uptake) and the environmental factors that affect stomatal conductance – solar radiation, CO2, air temperature, leaf temperature and humidity.

The water potential gradient that regulates water movement through trees is anchored by soil moisture availability on one end, and atmospheric moisture availability VPD on the other. VPD is indirectly estimated from measurements of relative humidity (RH) and air temperature (Tair) using micrometeorological sensors (Ewers and Oren, 2000). However, as Tleaf and Tair can differ by several degrees, the use of Tleaf instead of Tair to calculate VPD (1VPD) results in a more accurate representation of the true water vapor pressure gradient between the substomatal cavity and the boundary layer of the air near the leaf surface (Ewers and Oren, 2000). Therefore, Tleaf measurements are vital for better interpretation of plant hydraulic responses to environmental drivers in order to develop more accurate earth system models (ESMs) (Michaletz et al., 2016). However, sap velocity, Tleaf and environmental drivers are rarely measured together, especially in the tropics where the canopy layers are often hard to access (Chave et al., 2005; Segura and Kanninen, 2005). Thus, the response of a plant's transpiration to changes in environmental and physiological conditions remains highly uncertain in ESMs (Jasechko et al., 2013).

In relation to environmental drivers, clockwise hysteresis patterns between sap flow and VPD have been reported with higher sap flow rates during the morning period relative to the afternoon (O'Brien et al., 2004; Zeppel et al., 2004; Zhang et al., 2014). In addition, a counterclockwise hysteresis pattern has been observed in tropical and temperate forests when sap flow is plotted as function of irradiance (O'Brien et al., 2004; Zeppel et al., 2004; Bretfeld et al., 2018; Brum et al., 2018). In the case of transpiration, it has been established that the hysteresis phenomena are influenced by the temporal lag between solar radiation, which tends to peak in the late morning to mid-day, and VPD which tends to peak in the early afternoon (O'Brien et al., 2004; Zeppel et al., 2004; Zhang et al., 2014; Novick et al., 2016). Also, hysteresis between sap flux and environmental drivers are influenced by the stored stem water and the time lag between basal sap velocity and upper canopy transpiration, as an effect of hydraulic capacitance and resistance (Phillips et al., 1997; Ward et al., 2012). However, coupled field observations of physiological and environmental variables that include not only diurnal sap velocity and environmental driving data, but also concurrent leaf level data such as gs , Tleaf and 9L has been very limited in the tropics. Yet such data, are needed to verify

the relationships between Vs and environmental/physiological drivers in tropical forests.

In this study, we present in situ field observations of environmental (direct solar radiation, Tair and VPD) and physiological (Vs , gs , and 9L) variables and their correlations with Tleaf during the 2015–2016 ENSO. In order to observe the interactions between physiological variables and fast changing environmental conditions, we collected high temporal frequency data (15–60 min) in two primary rainforest sites located in the Eastern (Santarém) and in the Central (Manaus) Amazon. Since the 2015–2016 ENSO event was the warmest period in the Amazon forest over the past 13 years (Fontes et al., 2018), we expected peak Tleaf to increase and subsequently hysteretic behavior of water use vs. Tleaf to become more pronounced. In this study, we explored the mechanisms that regulate tree transpiration and the diurnal hysteresis patterns between physiological and environmental variables to contrast different tree species responses to the extreme 2015 dry season (ENSO) and a normal 2017 dry season ("control scenario").

### MATERIALS AND METHODS

#### Study Area

The field activities occurred in two sites near the cities of Manaus and Santarém, Brazil (**Supplementary Figure S1**). Near the city of Manaus, trees with leaves accessible from the K-34 walkup tower were selected for study. The 50-meter tall K-34 tower is located at the Reserva Biológica do Cuieiras, also known as ZF-2, and contains roughly 22,000 ha adjacent to extensive areas of undisturbed tropical forest (Araújo et al., 2002). The mean value of rainfall is ∼2,500 mm year−1 with the driest months of the year concentrated from July to September (Araújo et al., 2002). Field data were collected at the K-34 tower site between July 01, 2015 and December 01, 2017.

Near the city of Santarém, four trees near the K-67 triangle tower were selected for study, located in the Tapajós National Forest with approximately 527,000 ha near the Santarém-Cuiabá highway (BR-163). The K-67 tower is located ∼6 km west of the BR-163 and ∼6 km east of Tapajós river, in an area of largely contiguous forest from north to south (Hutyra et al., 2007). The site receives ∼2,000 mm year−1 of rainfall and has a five-month dry season from mid-July to mid-December (Saleska et al., 2003; Wu et al., 2017). In Santarém, field data were collected during the period of April 01, 2016 to December 31, 2016.

#### Species Selection

Different species were selected in a plateau area of Tapajós National Forest (Santarém) and Reserva Biológica do Cueiras (ZF-2 – Manaus) (eight species in total; **Table 1**). Tree selection criteria were based on the proximity of the crowns to the two canopy access towers (K-34 and K-67). This approach enabled measurement of physiological variables including sap velocity at breast height, Tleaf, gs , and 9L from leaves at the top of the crowns, together with environmental variables including direct solar radiation, Tair, and RH above the canopy (**Supplementary Figure S2**).

## Sap Velocity (Vs) Measurements

One heat pulse sap velocity sensor (SFM1, ICT international R ) was installed per tree near breast height (DBH) following the protocols previously described by Christianson et al. (2017). The SFM1 sensor consists of a heater and two temperature-sensing probes to determine sap velocity (cm h−1 ) at 0.75 cm depth in the stem using the heat ratio method (Burgess et al., 2001; Green et al., 2003; Steppe et al., 2010). The heater needle was configured to emit a 20 Joule pulse of thermal energy every 15 min (sap heat ratio measurements for 5 min 32 s following the pulse). Biophysical characteristics (diameter and bark thickness) for each tree were used as input into the Sap Flow Tool version 1.4.1 (Phyto-IT R ) to calculate sap velocity from raw data downloaded from the SFM1 sensors in the field.

The heat pulse method can be used for accurate measurements of sap flow (Lambers et al., 2008), but this method is unable to measure low rates due to its inability to distinguish heat-pulse velocities below a threshold velocity of 3–4 cm h−1 (Green et al., 2003). The probe spacing is also an important parameter and the sap velocity (Vs) is dependent upon the exact distance between needles as the following equation shows:

$$V\_S = \frac{k}{\varkappa} \ln\left(\frac{\nu\_1}{\nu\_2}\right) \* 3600 \text{ cm hr}^{-1} \tag{1}$$

where: k is the thermal diffusivity of wet wood; x is the distance between the heat source (heater) and temperature sensors; v1 and v2 are the increases in temperature (from ambient) at equidistant points downstream and upstream from the heater.

In this study, we used the factory default setting of 5 mm of needle spacings, as recommended by the manufacturer (Burgess and Downey, 2014), using a metal drill guide to ensure equidistant sensor placing. This 5 mm spacing is suitable to a theoretical maximum of 54 cm h−1 (Burgess and Downey, 2014).

It should be noted that following the protocols of 5 mm probe spacing of the SFM1 sensors, it is possible that the instrumental maximum was reached at relatively modest flows (16 cm h−1 for Pouteria anomala for example) on some days. Other available methods to estimate sap flow like the thermal dissipation method and the heat field deformation also underestimate Vs , where the error tends to increase with further increases in Vs (Steppe et al., 2010). However, evidence that the maximum observed Vs was not due to a sensor saturation includes: (1) different maximum values of Vs between species (plateau in the scatter plots); (2) the state theoretical maximum of 54 cm h−1 of the ICT user manual; and (3) on the same trees (Grossiord et al., under review) found no statistical difference between sap velocities determined by ICT and Granier sensors.

## Tleaf, Tair, VPD and Direct Solar Radiation Measurements

To measure Tleaf, a single infrared radiometer sensor (IRR SI-111 analogic for the species P. anomala, Pouteria erythrochrysa, and Couepia longipendula or IRR SI-131 digital for the species Eschweilera cyathiformis, Erisma uncinatum, Lecythis sp. and Chamaecrista xinguensis, Apogee R ) was positioned from the tower's structure with the field of view targeting the top of

TABLE 1 | List of tree species instrumented with sap velocity and Tleaf sensors in Manaus and Santarém.

Also, are shown the tree family, DBH, tree height, IRR viewing height, IRR viewing angle, and Tleaf target area. ∗Species with diurnal measurements of gs. ∗∗Species with diurnal measurements of 9L.

individual tree crowns (one IRR sensor per tree). Five-min averages of Tleaf were recorded using a CR-3000 (Campbell Scientific R for the SI-111 sensors) and EM-50 (Decagon R for the SI-131 sensors) dataloggers. The sensors were positioned with the viewing heights and viewing angles listed in **Table 1**. The field of view of each sensor (Tleaf target area) was calculated using the IRR calculator available in the website1 . To validate the infrared radiometer sensors installed on the two sites, Tleaf measurements were made using Teflon insulated type T thermocouples (OM-CP-OCTTEMP-A Nomad R , Omega Engineering) directly attached to the abaxial side of the leaf using a breathable white tape and configured to register measurements every 15 s (**Supplementary Figure S3**). In addition, in Manaus direct solar radiation (W m−2 ) with 5-min averages were collected at 35.0 m above the canopy using a SPN1-Sunshine Pyranometer (Delta-T Devices R ). Tair and RH data were obtained using a thermohygrometer (HC2S3, Campbell Scientific R ) installed above the canopy at 51.1 m height on the K-34 tower structure.

In this study, a more accurate physiological approach to estimate VPD was applied. The Tetens equation was used to calculate the saturation vapor pressure of the air (eo) using the variables air temperature (Tair) and relative humidity of the air (RHo) (Eq. 2). To estimate the saturation vapor pressure inside the substomatal chamber (ei) the Tetens equation was also used replacing Tair by Tleaf (Eq. 3). The relative humidity inside the substomatal cavity (RHi) was assumed to be equal to 1 as demonstrated by many studies (Ward and Bunce, 1986; Buckley et al., 2017; Cernusak et al., 2018). With these variables it was possible to estimate the VPD difference between the substomatal chamber (ei × RHi) and the atmosphere (eo × RHo) (Eq. 4).

$$e\_0 = 0.611 \times 10^{\left(\frac{7.5 \times \text{Tair}}{\text{Tair} + 237.9}\right)}\tag{2}$$

$$e\_i = 0.611 \times 10^{\left(\frac{7.5 \times Tlaq^{\circ}}{Tlaq^{\circ} + 237.3}\right)}\tag{3}$$

$$
\Delta VPD = \ (e\_i \times RH\_i) - \ (e\_o \times RH\_o) \tag{4}
$$

where: 1VPD is the leaf-to-air water VPD (kPa); eo is the air saturated water vapor pressure (kPa); ei is the saturated water vapor pressure inside the substomatal chamber (kPa); RHi is the relative humidity inside the substomatal cavity which is assumed to be equal to 1. RHo is the relative humidity of the air near the leaf surface (expressed as a decimal); Tleaf is the leaf temperature in ◦C and Tair is the air temperature in ◦C.

#### Stomatal Conductance (gs) Measurements

Diurnal observations of gs were made on upper canopy leaves accessible from the walkup towers (K-34 in Manaus and a walkup tower 1 km from the K-67 triangle tower in Santarém). In Manaus, diurnal patterns of gs were measured from individual leaves at the top the main crown near the towers from 6:00 to 18:00 using a Li-Cor 6400 XT portable photosynthesis system (Li-Cor, Lincoln R , NE, United States). gs measurements on individual leaves were made for 10 min using Li-Cor 6400 XT. The CO2 reference concentration was held constant at 400 µmol mol−1 . Tblock and photosynthetically active radiation values were set every 15 min to match environmental conditions. Using the Li-Cor 6400 XT we set the Tblock to achieve a target Tleaf, based on the infrared radiometers measurements recorded in the CR-3000 datalogger which have a screen that makes possible real time data reads without a computer. In Santarém, gs measurements on individual leaves were made every 2 min using the SD-1 leaf porometer system (Decagon Devices R , WA, United States) throughout the day.

## Leaf Water Potential (9L) Measurements

In Manaus 9L data were collected from three trees together with Tleaf measurements (**Table 1**) to access potential diurnal hysteresis patterns similar to those observed with sap velocity, gs , Tair, Tleaf, and 1VPD. Hourly 9L measurements (6:00 to 18:00 – 12 h) of healthy leaves without noticeable condensation on the surface of P. anomala, P. erythrochysa, and C. longipendula were performed in Manaus using a pressure chamber instrument (Model 1000, PMS Instrument Company R ) connected to a highpressure nitrogen cylinder. Small branches from the upper tree crowns were removed and a single leaf per tree was used to measure 9L. The canopy position of each tree was also classified following the crown illumination index proposed by

1https://www.apogeeinstruments.com/irr-calculators/

Synnott (1979) (**Supplementary Table S1**). In this study, the leaf water potential measurements were performed in a single day of September during both 2015 and 2017 dry season.

#### Data Analysis

fpls-10-00830 June 27, 2019 Time: 19:2 # 5

Data were analyzed using IGOR Pro R version 6.3 (WaveMetrics, Inc., United States) and R v. 3.0.2 (R Development Core Team, 2013) software packages. In Manaus, 4-month time series (August to November) were plotted to observe the correlations between Tleaf and Tair during the 2015 dry season (ENSO). Additionally, the two-dimensional kernel density function (kde2d) was used to observe potential offsets between Tleaf and Tair during the 2015 dry season. In Manaus, the 2015 dry season (ENSO period) was compared with the 2017 dry season ("control scenario") using hysteresis indexes (Hindex) of the normalized values of Tleaf, Tair, and 9L for the species P. anomala, C. longipendula, and P. erythrochrysa. For the normalization of each variable the min-max feature scaling method was used to standardize the range of the raw data. Hysteresis indices were calculated using the shoelace formula (Eq. 5; Braden, 1986), and a paired t-test was performed (α = 0.05) to intercompare the Hindex of the species between the 2015 and 2017 dry seasons. The Hindex is a measure of the size of the hysteresis loop and enables quantitative comparisons of hysteresis behaviors during, for example, two contrasting periods like El Niño and regular season.

$$A = \frac{1}{2} \left| \sum\_{\mathbf{i}=1}^{n} \mathbf{x}\_{\mathbf{i}} \mathbf{y}\_{\mathbf{i}+1} + \mathbf{x}\_{\mathbf{n}} \mathbf{y}\_{1} - \sum\_{\mathbf{i}=1}^{n} \mathbf{x}\_{\mathbf{i}} \mathbf{y}\_{\mathbf{i}+1} - \mathbf{x}\_{\mathbf{n}} \mathbf{y}\_{1} \right| \tag{5}$$

where: A is the area of the polygon, n is the number of sides of the polygon, and (xi , yi), i = 1, 2, . . . , n are the vertices (or "corners") of the polygon.

Additionally, normalized sap velocity and Tleaf hysteresis parameters of the species E. cyathiformis, P. anomala, and P. erythrochysa were compared separating the morning and afternoon/night periods during both 2015 and 2017 dry seasons (ENSO and regular season). In the morning period sigmoidal curves were fitted using 15 min interval data of the variables Vs and Tleaf. The statistical parameters of the sigmoidal curves were used to compare the ENSO and the regular season between species. The same approach was done to compare the afternoon/night period of the variables Vs and Tleaf but using power curves instead of sigmoidal functions.

## RESULTS

## Vs, Tleaf, and 1VPD

Representative four-day time series of Vs as function of Tleaf and 1VPD for E. cyathiformis in Manaus and Vs as function of Tleaf for Lecythis sp. in Santarém are presented in **Figure 1**. Despite expectations of a significant delay due to the large vertical distance between the observations of Vs and Tleaf, the two variables tightly track each other, during the day and night (**Figures 1A,E**). Additionally, normalized time series of Vs and Tleaf of six trees during a two-month period also show this tightly

FIGURE 1 | Four-day time series showing the daily patterns of sap velocity (Vs), leaf temperature (Tleaf), and vapor pressure deficit (1VPD) for the species Eschweilera cyathiformis, Pouteria anomala, and Lecythis sp. Example of temporal similarities between Vs and Tleaf are shown in (A,E). Temporal similarities were also observed for Vs and 1VPD (B). A temporal decoupling during the afternoon period was observed between Vs and direct solar radiation (C). The contrasting patterns of direct solar radiation and Tleaf are also shown in (D).

temporal track (**Supplementary Figure S4**). Moreover, temporal similarities were also graphically observed for the variables Vs and 1VPD (**Figure 1B**).

2015, Tleaf reached, in some days, more than 40◦C for all studied species (D–F). In general, during the 2015 ENSO, maximum values of Tleaf for all species were higher than maximum values of Tair. However, during some days at the end of the 2015 dry season, Tair was higher than Tleaf for the species C. longipendula and

Diurnal patterns of direct solar radiation differed from those of Tleaf in Manaus, especially during the afternoon period (**Figure 1D**). Direct solar radiation peaked about mid-day, then declined during the afternoon. In contrast, Tleaf and 1VPD patterns peaked later, during the early afternoon and maintained high values until late afternoon even as solar radiation declined (**Figures 1A–E**). Thus, for Manaus, on average, a lag of 2 h and 22 min delay occurred between the peaks of direct solar radiation and Tleaf.

## Tleaf and Tair Relations

P. erythrochrysa (D,F).

The highest Tleaf values during the ENSO in the year of 2015 (2015 dry season – August to November) were observed during the months of September and October (**Figure 2**). On some days during the 2015 dry season, the differences between Tleaf and Tair were close to 8◦C for some species (average difference between Tleaf and Tair for all species: 1.65 ± 1.07◦C). For the species C. longipendula (**Figure 2A**) the maximum observed Tleaf value was 40.78◦C (September 12, 2015 – 11:30 local time) and the difference between Tleaf and Tair was on average 1.70 ± 1.20◦C (maximum observed difference 7.43◦C); for the species P. anomala (**Figure 2B**) the maximum observed Tleaf value was 40.09◦C (September 22, 2015 – 15:30 local time) and the difference between Tleaf and Tair was in average 1.49 ± 0.92◦C (maximum observed difference 7.26◦C); for the species P. erythrochrysa (**Figure 2C**) the maximum observed Tleaf value was 39.67◦C (October 4, 2015 – 13:30 local time) and the difference between Tleaf and Tair was in average 1.75 ± 1.06◦C (maximum observed difference 6.39◦C). At the end of the 2015 dry season (November), there were some days when Tair reached higher values compared to Tleaf for the species C. longipendula and P. erythrochrysa (**Figures 2D,F**). The 1:1 baseline presented in **Figures 2A–C** provides a reference to examine deviations of Tleaf from Tair, where the densest observations are between 23 and 26◦C with the majority of Tleaf values lower than Tair. This pattern is observed during the night period, when the lowest Tair and Tleaf values are recorded. In addition, hysteresis patterns between Tleaf and Tair were observed for the species P. anomala, C. longipendula, and P. erythrochrysa in Manaus during the 2015 and 2017 dry season (**Figure 3**). The area of the hysteresis loops (Hindex) of P. anomala, C. longipendula and P. erythrochrysa during the 2015 dry season (ENSO) were statically larger (p < 0.01, α = 0.05, paired t-test) than the 2017 dry season ("control scenario"; **Figure 3**). The Hindex of the normalized variables Tleaf and Tair of the species P. anomala, C. longipendula and P. erythrochrysa during the 2015 dry season was, respectively: 0.0633; 0.0747; 0.0904. Moreover, the Hindex calculated for P. anomala, C. longipendula, and P. erythrochrysa for the 2017 dry season was, respectively: 0.0355; 0.0406; 0.0523.

Using hourly averages for all the analyzed species it was possible to observe that generally Tleaf was higher than Tair from the middle of the morning period until the early afternoon in both the 2015 and 2017 dry seasons (**Figure 3**). In contrast, Tair was predominantly higher than Tleaf in the early morning, middle afternoon, and throughout the night in both the 2015 and 2017 dry seasons.

FIGURE 3 | Hourly averages of Tleaf and Tair for the species C. longipendula, P. anomala, and P. erythrochrysa in Manaus site during the 2015 dry season (ENSO) and 2017 dry season ("control scenario"). The clockwise hysteresis pattern between Tleaf and Tair was observed for all the studied trees in Manaus. The orange dots represent the morning period (6:00–12:00), the red dots represent the afternoon period (13:00–19:00), and the blue dots represent the night period (20:00–5:00) (A,B,D,E,G,H). A significant difference (p < 0.01) of Tleaf and Tair hysteresis loops (Hindex) was observed when the 2015 dry season (ENSO period) was compared with the 2017 dry season ("control scenario") (C,F,I). On average, in both 2015 and 2017 dry season, Tleaf was higher than Tair during the middle morning to early afternoon, and Tair was higher than Tleaf in the middle afternoon, night and early morning. The exception was for the species P. erythrochrysa where, on average, during the 2017 dry season Tleaf was higher than Tair only during the morning period (08:00–10:00) (H).

species in Manaus (A–C), and Santarém (D–F). The hysteresis phenomenon is represented by a single day of data randomly selected, separated by morning (orange values, 6:00–14:00), afternoon (red values, 14:15–19:00), and nighttime (blue values, 19:15–5:45) periods.

## Vs−Tleaf, Vs−1VPD, and Vs-Direct Solar Radiation Diurnal Hysteresis

As an example, 1 week of Vs data were plotted as function of Tleaf, 1VPD and direct solar radiation (**Figures 4**, **5**). The clockwise hysteresis in Vs−Tleaf and Vs−1VPD was evident with morning periods showing higher temperature sensitivities than afternoon and night periods and in this study is referred to as the "gs effect" (**Figures 4**, **5**). In Manaus, the scatter plot of Vs-direct solar radiation revealed a counterclockwise hysteresis pattern, on the same day as the Vs−1VPD clockwise hysteresis (**Figure 5**). For the same direct solar radiation values, higher Vs values in the afternoon were observed relative to the morning period, and in this study this pattern is referred to as the "VPD effect."

Vs showed a sigmoid dependence on Tleaf and 1VPD including a rapid increase, an inflection point, and a plateau. When Vs reached the maximum values for each species, it was insensitive to further increases in Tleaf and 1VPD (**Figure 6** and **Supplementary Figure S5**). The sigmoid pattern was observed in all studied trees (**Supplementary Figure S5**), although the maximum Vs differed between species from 8 to 24 cm h−1 ; detailed daily patterns of Vs−Tleaf revealed a sigmoid increase in Vs during the morning period followed by an exponential decrease in the afternoon and throughout the night (**Figure 6**). During the morning period the curve's maximum values (max) of the sigmoid function for the variables Tleaf and Vs were lower when the 2015 dry season (ENSO) was compared to the 2017 dry season (regular) for the species E. cyathiformis and P. erythrochrysa (**Figure 7**) (curve's maximum values (max): E. cyathiformis ENSO (2015): 0.6379 ± 0.017; E. cyathiformis regular dry season (2017): 0.9376 ± 0.028; P. erythrochrysa ENSO (2015): 0.6992 ± 0.029; P. erythrochrysa regular dry season (2017): 0.8837 ± 0.029). For the species P. anomala the max was statistically equal in both periods (curve's maximum values (max): P. anomala ENSO (2015): 0.7386 ± 0.082; P. anomala regular dry season (2017): 0.6960 ± 0.024). The inflection point (xhalf) of the sigmoidal curves also revealed different patterns between species. The xhalf values were lower for the species E. cyathiformis and P. anomala during the 2015 ENSO in comparison to the 2017 regular dry season (inflection point (xhalf): E. cyathiformis ENSO (2015): 0.3433 ± 0.006; E. cyathiformis regular dry season (2017): 0.5401 ± 0.006; P. anomala ENSO (2015): 0.2648 ± 0.024; P. anomala regular dry season (2017): 0.3423 ± 0.008. In

similar temporal patterns with gs by circadian cycles.

contrast the xhalf value for the species P. erythrochrysa was higher during the ENSO in comparison to the 2017 regular dry season (inflection point (xhalf): P. erythrochrysa ENSO (2015): 0.4253 ± 0.012; P. erythrochrysa regular dry season (2017): 0.3064 ± 0.007). The statistical values of the power function during the afternoon/night period was relatively similar in both ENSO and regular dry season for the species E. cyathiformis and P. anomala (**Figure 7**). The exception was the species P. erythrochrysa which the exponent parameter (pow) were higher during ENSO compared to the 2017 regular dry season.

## gs−Tleaf and 9L−Tleaf Diurnal Hysteresis

Clockwise hysteresis patterns were observed for gs-Tleaf in Manaus and Santarém (**Supplementary Figure S6**). For the same Tleaf, the observed gs values of E. cyathiformis and Manilkara sp. were greater during the morning period than the afternoon. The maximum observed gs values occurred at a Tleaf of 33.3◦C in Manaus and 32.6◦C in Santarém (**Supplementary Figure S6**).

A counterclockwise hysteresis pattern was observed between 9L and Tleaf (**Figure 8**). At the same Tleaf values, 9L were more negative in the morning compared to the afternoon period. During September 2015 (peak of the El Niño) the Hindex of the variables 9L and Tleaf were significantly higher compared to September 2017 (regular dry season) (p < 0.01, α = 0.05). The Hindex calculated for the species P. anomala, C. longipendula, and P. erythrochrysa during the 2015 dry season was, respectively: 0.2379; 0.3116; 0.1605. Moreover, the Hindex calculated for P. anomala, C. longipendula, and P. erythrochrysa for the 2017 dry season was, respectively: 0.0642; 0.1596; 0.0324.

## DISCUSSION

## Correlations Between Sap Velocity, Tleaf, Tair and 1VPD

With a fine-scale measurement resolution of 15 min, temporal similarities between Vs and Tleaf were observed for all studied species. Delays between Vs−Tleaf and Vs−1VPD, are expected due to the large differences in the heights of the measurements (basal sap velocity versus Tleaf in the upper canopy). This type of delays are related to the capacitance of the stems, where the evaporative demand in the branches near the crown are greater than the basal portions of the trunk, with an observed lag in the morning period between these two portions of the tree (Meinzer et al., 2003). Future research should aim to quantify these delays, using for example, simultaneous measurements of Vs at DBH height and Vs in the branches near the crown, as in Goldstein et al. (1998). At a small time resolution, similar results

were previously observed using Granier sap flow system and micrometeorological sensors in French Guiana (Granier et al., 1996), and North Carolina, United States (Oren et al., 1999a). At both sites (F. Guiana and N. Carolina), similar temporal correlations were observed between sap flow and VPD using a measurement resolution of 30 min. A recent study of Bretfeld et al. (2018) showed that Vs is largely in phase with VPDair in an 80 year-old-forest which is similar to the observed results of this study. In addition, sigmoid patterns between Vs−VPD and Vs−Tleaf were also observed for all studied trees (**Supplementary Figure S5**), as also observed by O'Brien et al. (2004) in tropical species of Costa Rica, and da Costa et al. (2018) in the eastern Amazon. In this study, sap velocity displayed species-specific diurnal hysteresis patterns with a sigmoidal increase during the morning period and an exponential decrease during the afternoon/night period, with statistical differences between the extreme 2015 dry season (ENSO) and a normal 2017 dry season ("control scenario") (**Figures 6**, **7**).

Given the large diurnal Tleaf variation and the exponential dependence of VPD on Tleaf (Eqs 2, 3), changes in VPD during the daytime are largely driven by changes in Tleaf (Jackson et al., 1981; Ewers and Oren, 2000). The relationship between Tleaf and Tair represented by Tleaf−Tair offset is a good indicator of water stress in plants (Jackson et al., 1981). Over short time scales (e.g., 10 s) Tleaf is also partially related to the leaf mass per area (Michaletz et al., 2016), which can provide new insights about the water dynamics like capacitance. Low temperature values during rainstorms are associated with low VPD and high RH in the Amazon forest (Moradi et al., 2016). Periods of days with the lowest observed Vs are related to the lowest observed values

#### FIGURE 7 | Continued

P. erythrochrysa during 2015 (ENSO) and 2017 (regular) dry seasons. During the morning period the curve's maximum values (max) of the sigmoid function for variables Vs and Tleaf were lower during the 2015 dry season (ENSO) in comparison to the 2017 dry season (Regular) for the species E. cyathiformis and P. erythrochrysa and statically equal for the species P. anomala (A,C,E,G,I,K). The inflection point (xhalf) of the sigmoidal curves also revealed different patterns for the species when the 2015 dry season was compared to the 2017 dry season. The xhalf values were lower for the species E. cyathiformis and P. anomala during the 2015 ENSO in comparison to the 2017 regular dry season (A,C,E,G). In contrast the xhalf value for the species P. erythrochrysa was higher during the ENSO in comparison to the 2017 regular dry season (I,K). The statistical values of the power function during the afternoon/night period were relative similar in both ENSO and regular dry season for the species E. cyathiformis and P. anomala (B,D,F,H). The exception was the species P. erythrochrysa which the exponent parameter (pow) where higher during ENSO compared to the 2017 regular dry season (J,L).

of Tleaf and 1VPD. This observation is consistent with previous studies in the Amazon where rain, cloud coverage, and reduced direct solar radiation were found to be the major factors that reduced xylem sap flow rates (Kunert et al., 2017). In addition, other researchers in tropical sites like Costa Rica found that significant leaf wetness also reduces sap flow by up to 28% by impacting VPD (Aparecido et al., 2016).

The positive nighttime Vs observed in Manaus and Santarém also apparently followed Tleaf, similar to that observed by Burgess and Dawson (2004) which found strong positive similarities between nighttime sap flow and VPD in Sequoia sempervirens. These observations of positive nighttime Vs in the first hours of the night are probably related to the capacitance of stem tissues and radial water transport (Steppe et al., 2012), as well as incomplete stomatal closure (Snyder et al., 2003; Barbour and Buckley, 2007; Dawson et al., 2007) which also allows trees to increase their water content through foliar water uptake (Eller et al., 2013). Another explanation for nighttime transpiration is the water outlet through lenticels, small pores on stem surfaces of many tropical tree species (Roth, 1981). However, it should be noted that no treatment was done to correct Vs for small potential offsets (less than 1 cm h−1 – lower scales) to estimate the standard deviation of Vs, and the possibility of positive nighttime water flow where, in this study, the Vs values are generally close to zero.

#### Hysteresis Patterns

In the current study, clockwise hysteresis patterns were observed for Vs−Tleaf and Vs−1VPD (**Figures 4**, **5**). Similar results were previously described for sap flow and VPD in tropical forests of Costa Rica (O'Brien et al., 2004) and in tropical secondary forests in Panama (Bretfeld et al., 2018), in temperate forests of Australia (Zeppel et al., 2004), in eastern Amazon trees (Brum et al., 2018) and in a grass-land ecosystem (Zhang et al., 2014). The observed hysteresis phenomenon for sap velocity has been described as a result of the temporal offset of gs that tends to peak, in the tropics, during late morning to mid-day (10:30–12:00) (Slot and Winter, 2017a) (**Supplementary Figure S6**) and VPD that tends to peak in the early afternoon (13:00–14:30). The hysteresis phenomenon can also be visualized with variables Tleaf and direct solar radiation (irradiance). In normal conditions gs

respond positively to irradiance (Hennessey and Field, 1991; Gorton et al., 1993; Motzer et al., 2005) and the temporal similarities between these two variables are supposed to be associated with circadian cycles (daily patterns), as demonstrated in some hysteretic behaviors of this study separating the morning, afternoon, and night periods.

In terms of temperature, gs was found to reach a maximum at a Tleaf of 31–33◦C, which relates with the optimum temperature for photosynthesis (Topt) previously determined for many tropical species (Slot and Winter, 2017b). Interestingly, this Topt range seems to match with the inflection point (xhalf) in the Vs−Tleaf hysteresis plots in Manaus (**Figures 4–7**). Thus, we speculate that it may be possible to determine Topt using Vs−Tleaf diurnal hysteresis plots for individual trees. The observed inflection points patterns of Vs−Tleaf during the morning period for the species E. cyathiformis, P. anomala, and P. erythrochrysa (**Figure 7**) seems to be influenced by the canopy position and the resistance to drought once, in this study, species-specific shifts emerged when the 2015 ENSO was compared to the 2017 dry season. Additionally, the calculation of an index to quantify the hysteresis loops (Hindex) was performed by this study, similar to a previous approach of Zuecco et al. (2016) which described hysteresis patterns of hydrological variables and runoff events. A quantitative comparison of hysteresis loops from a large number of species using an index approach would be a way of constraining ranges of hysteresis effects in models. Satellite observations revealed that September 2015 exhibited the warmest monthly averaged surface air temperature of any other month over the past 13 years in the Central Amazon (Fontes et al., 2018). These extreme temperatures also modified Tleaf patterns, as observed by this study (**Figure 3**). Higher Tleaf values were reflected in a significantly higher Hindex for the variables Tleaf−Tair and 9L−Tleaf when the 2015 dry season (ENSO period) was compared to the 2017 dry season ("control scenario"). Even though Hindex for Vs was not calculated in this study, we found species-specific shifts in diurnal sap velocity dynamics in both 2015 and 2017 dry seasons contradicting the expected higher values of transpiration during 2015 ENSO compared to other periods due to the high evaporative demand. Brum et al. (2018), for example, found significant differences in the Hindex for transpiration between dry and wet seasons during the 2015– 2016 ENSO in the Eastern Amazon. Nevertheless, the effect of gs during drought events needs to be clarified because trees are expected to show a strong stomatal control under drought conditions, which would offset the expected increase in transpiration Hindex. The higher Tleaf values compared to Tair during the middle morning to early afternoon observed by this study for the species P. anomala, C. longipendula, and P. erythrochrysa also contradicts with the expected decrease in Tleaf due the transpiration effect. One possible explanation for this pattern is the leaf flushing which is, in the Central Amazon, concentrated in the five driest months (Lopes et al., 2016). On this period, it is possible that the leaf photosynthesis apparatus and tissues aren't fully developed, reflecting directly in the gs and transpiration patterns. Also, the increasing of light availability in the Amazon forest during the dry season can, maybe, exert an overriding effect in Tleaf patterns relative to the cooling effect of transpiration.

Changes in gs are associated with changes in 9L via their mutual effects on the balance between Vs and transpiration rates. Consistent with the clockwise hysteresis between Vs−Tleaf and Vs−1VPD, a counterclockwise hysteresis pattern was observed between 9L−Tleaf. At the same Tleaf, 9L were more negative during morning than afternoon suggesting that partial stomatal closure in the afternoon allows the leaf to recover to less negative 9L (**Figure 8**; Jarvis, 1976). The results suggest that during 2015–2016 ENSO the trees of this study located in a plateau area have a strong isohydric behavior, by reducing stomatal conductance in the warm afternoon periods in order to reduce transpiration rates, thereby minimizing the chances for embolism (Sade et al., 2012; Roman et al., 2015). The same process can be observed in the clockwise hysteresis between Vs−Tleaf, and Vs−1VPD where the partial stomatal closure in the afternoon period reduce the Vs rates compared to the morning (**Figures 4**, **5**). In this study this pattern was called the "gs effect." It should be emphasized that the daily hysteresis patterns with the morning, afternoon and night periods separated by colors make it possible to observe both the "gs effect" and "VPD effect" (**Figure 5**).

Interestingly, the counterclockwise hysteresis pattern of Vs-direct solar radiation is not driven by the partial stomatal closure in the late morning until the afternoon period, but by the high 1VPD. At the same solar radiation intensity, higher Vs occurs during the afternoon relative to the morning and in this study was called the "VPD effect" (**Figure 5**). This observations suggests that partial stomatal closure in the afternoon can be offset by the effect of high 1VPD in maintaining elevated transpiration rates under high afternoon temperatures, as previously shown in other ecosystems (O'Brien et al., 2004; Zeppel et al., 2004; Zhang et al., 2014; Novick et al., 2016; Bretfeld et al., 2018; Brum et al., 2018). Also, these results support recent findings that heat waves can be associated with sustained transpirational cooling as a key mechanism of thermotolerance (Drake et al., 2018). However, the mechanisms of transpiration cooling can be exceeded by the heat intensity during El Niño events, which increase tree mortality in the Amazon forest (Aleixo et al., 2019). Finally, the range of Hindex for the variables Tleaf and Tair presented for the first time in this study, can be a useful tool to predict future impacts on tree mortality during extreme drought events in comparison to other periods.

The observed differences of the maximum Vs rates (curve's maximum values (max) of sigmoidal functions during the morning period – **Figure 7**)) between species can be related to the diameter of the vessels (Dünisch and Morais, 2002), wood density (Eller et al., 2018) and with the susceptibility to embolism (Lovisolo and Schubert, 1998). Tree height is also an important factor which influences sun exposure and therefore the temperature of the leaves and transpiration rates (Goldstein et al., 1998). In Manaus, E. cyathiformis was the thinnest and shortest studied tree with 14.3 cm of DBH and 19.8 m of height and was the tree with the lowest observed Vs rates

Gimenez et al. Hysteresis Patterns Amazon Forest Environment

(∼8 cm h−1 ) during ENSO (**Figure 4**). In contrast, the Pouteria genus (P. anomala and P. erythrochysa) have large DBHs (35.3 cm and 36.5 cm) and high rates of Vs during ENSO (18 and 12 cm h−1 , respectively) (**Figure 4**). This is consistent with other studies where DBH, height and sap flow showed a positive correlation (Motzer et al., 2005). Likewise, the same correlations were observed in Santarém, where the larger DBHs showed the higher sap velocity. Also, the observed differences in curve's maximum values (max) of sigmoidal curves observed for Vs and Tleaf during ENSO period and the regular dry season (**Figure 7**), may be associated with the high range of functional traits and susceptibility to embolism of some trees in the Amazon forest along hydro-topographic gradients (Cosme et al., 2017; Oliveira et al., 2019). Other important issue is that mortality rates during droughts are substantially higher for large DBH's (Meakem et al., 2017), and maybe this is potentially aggravated by high transpiration rates and the crown exposure to the direct light. Another study of rain exclusion in the eastern Amazon by Rowland et al. (2015) support this observation. However, other factors are also involved since it has been shown that earlysuccessional forests experienced more drought stress than trees in late-successional forests (Bretfeld et al., 2018). In fact, more studies are needed in the tropics, especially in the Amazon, due to the large diversity of terrestrial plants (Ter Steege et al., 2013), the wide range of functional traits and evolutionary strategies to avoid cavitation, carbon starvation, and other aspects related to drought which can modify Tleaf and Vs patterns.

#### CONCLUSION

For the first time in the Amazon forest, the quantitative differences and the hysteresis pattern between Tleaf and Tair were demonstrated and compared during the 2015 (ENSO) and 2017 ("control scenario") dry seasons. The relationship between Tleaf and Tair was significantly different between these two periods and, in general, Tleaf was higher than Tair during the middle morning to early afternoon. The use of the variable Tleaf together with Tair are extremely important to ecophysiological observations due to the differences in terms of magnitude and temporal patterns. Also, Tleaf is an important variable to estimate the true water vapor pressure gradient between the substomatal cavity and the boundary layer of the air near the leaf surface (1VPD). Moreover, sap velocity displayed species-specific diurnal hysteresis patterns that were strongly linked to gs and VPD and reflected by changes in Tleaf. In the morning, gs was linearly related to Tleaf and sap velocity displayed a sigmoidal relationship with Tleaf. In the

#### REFERENCES

afternoon, stomatal conductance declined as Tleaf approached a daily peak, allowing 9L to begin recovery, while sap velocity declined with an exponential relationship with Tleaf. Hysteresis indices (Tleaf : Tair and Tleaf : 9L) were much more pronounced during the ENSO event than during a typical dry season and varied between species, which reflects species-specific capacitance and tree hydraulic traits. Future research may address a new modeling approach using the magnitude of the hysteresis loops (Hindex) to measure, for example, the intensity of the droughts and how it impacts plant communities. Finally, the hysteretic behavior of the transpiration separated by morning, afternoon and night periods is the key to understand the complexity of this process in a changing climate and improve the current models.

#### AUTHOR CONTRIBUTIONS

BG, KJ, RN-J, IS-F, CF, LC, JH, JC, NH, TD, and NM performed the experiments and analyzed the data. JC, NH, TD, and NM planned and designed the experiments. BG and KJ wrote the manuscript. CF, AA, JW, BN, CV, DC, GS, CK, and NM improved the manuscript.

#### FUNDING

This material is based upon work supported as part of the Next Generation Ecosystem Experiments-Tropics (NGEE-Tropics), as part of DOE's Terrestrial Ecosystem Science Program – Contract No. DE-AC02-05CH11231. Additional funding for this research was provided by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

## ACKNOWLEDGMENTS

The authors are thankful to the logistical and scientific support provided by the Laboratório de Manejo Florestal (LMF) and the Large-Scale Biosphere-Atmosphere Program (LBA) at the National Institute of Amazonian Research (INPA).

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2019.00830/ full#supplementary-material

conductance. Plant Cell Environ. 30, 711–721. doi: 10.1111/j.1365-3040.2007. 01658.x

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Gimenez, Jardine, Higuchi, Negrón-Juárez, Sampaio-Filho, Cobello, Fontes, Dawson, Varadharajan, Christianson, Spanner, Araújo, Warren, Newman, Holm, Koven, McDowell and Chambers. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Genotypic, Developmental and Environmental Effects on the Rapidity of gs in Wheat: Impacts on Carbon Gain and Water-Use Efficiency

Michele Faralli1 , James Cockram2 , Eric Ober2 , Shellie Wall1 , Alexander Galle3 , Jeroen Van Rie3 , Christine Raines1 and Tracy Lawson1 \*

1 School of Biological Sciences, University of Essex, Colchester, United Kingdom, 2 The John Bingham Laboratory, NIAB, Cambridge, United Kingdom, 3 BASF Agricultural Solutions Belgium NV, Ghent, Belgium

#### Edited by:

Stuart Anthony Casson, The University of Sheffield, United Kingdom

#### Reviewed by:

Shardendu Kumar Singh, United States Department of Agriculture, United States Caspar Christian Cedric Chater, The University of Sheffield, United Kingdom

> \*Correspondence: Tracy Lawson<EMAIL_ADDRESS>
#### Specialty section:

This article was submitted to Plant Physiology, a section of the journal Frontiers in Plant Science

Received: 07 September 2018 Accepted: 01 April 2019 Published: 17 April 2019

#### Citation:

Faralli M, Cockram J, Ober E, Wall S, Galle A, Van Rie J, Raines C and Lawson T (2019) Genotypic, Developmental and Environmental Effects on the Rapidity of gs in Wheat: Impacts on Carbon Gain and Water-Use Efficiency. Front. Plant Sci. 10:492. doi: 10.3389/fpls.2019.00492 Stomata are the primary gatekeepers for CO2 uptake for photosynthesis and water loss via transpiration and therefore play a central role in crop performance. Although stomatal conductance (gs) and assimilation rate (A) are often highly correlated, studies have demonstrated an uncoupling between A and gs that can result in sub-optimal physiological processes in dynamic light environments. Wheat (Triticum aestivum L.) is exposed to changes in irradiance due to leaf self-shading, moving clouds and shifting sun angle to which both A and gs respond. However, stomatal responses are generally an order of magnitude slower than photosynthetic responses, leading to nonsynchronized A and gs responses that impact CO2 uptake and water use efficiency (iWUE). Here we phenotyped a panel of eight wheat cultivars (estimated to capture 80% of the single nucleotide polymorphism variation in North–West European bread wheat) for differences in the speed of stomatal responses (to changes in light intensity) and photosynthetic performance at different stages of development. The impact of water stress and elevated [CO2] on stomatal kinetics was also examined in a selected cultivar. Significant genotypic variation was reported for the time constant for stomatal opening (Ki , P = 0.038) and the time to reach 95% steady state A (P = 0.045). Slow gs opening responses limited A by ∼10% and slow closure reduced iWUE, with these impacts found to be greatest in cultivars Soissons, Alchemy and Xi19. A decrease in stomatal rapidity (and thus an increase in the limitation of photosynthesis) (P < 0.001) was found during the post-anthesis stage compared to the early booting stage. Reduced water availability triggered stomatal closure and asymmetric stomatal opening and closing responses, while elevated atmospheric [CO2] conditions reduced the time for stomatal opening during a low to high light transition, thus suggesting a major environmental effect on dynamic stomatal kinetics. We discuss these findings in terms of exploiting various traits to develop ideotypes for specific environments, and suggest that intraspecific variation in the rapidity of stomatal responses could provide a potential unexploited breeding target to optimize the physiological responses of wheat to dynamic field conditions.

Keywords: stomatal rapidity, Triticum aestivum L., photosynthesis, stomatal conductance, water-use efficiency, water stress, elevated [CO2]

**20**

## INTRODUCTION

fpls-10-00492 April 15, 2019 Time: 17:39 # 2

Wheat (Triticum aestivum L.) is one of the most important food crops globally, accounting for 20% of human calorie consumption (Ray et al., 2013). Significant yield gains have been achieved in the last century following both genetic improvements and advances in crop management (Slafer et al., 2015). However, more recently, evidence of stagnation in yield improvement, combined with the predicted environmental changes associated with global warming (Ray et al., 2012), highlight the need to identify optimized crop ideotypes and new genetic targets for incorporation into current wheat breeding programs to maintain and/or improve future productivity.

Crop yield is the product of the cumulative rates of photosynthesis over the growing season and the subsequent capacity of sinks to accept and store these products (Zelitch, 1982). Although previous work suggested that selecting for elevated photosynthetic rate on a leaf area basis does not always produce significant results in terms of yield (Evans, 1996), freeair concentration enrichment experiments (Long et al., 2006) and bioengineering approaches (Driever et al., 2017) have provided promising results, and highlight the possibility of yield gains via elevated rates of photosynthesis. In many crops, while harvest index and light interception capacity are approaching theoretical maximum (∼0.64 and 0.8–0.9 respectively, Long et al., 2006), the efficiency of energy conversion into biomass (i.e., radiationuse efficiency and thus photosynthesis) still has substantial room for improvement (Long et al., 2006). Most of the intraspecific natural variation in photosynthesis for C3 plants is mainly due to differences in biochemical capacity including electron transport rates and carboxylation efficiency (Driever et al., 2014; Carmo-Silva et al., 2017). In addition, under natural dynamic conditions photosynthetic process can also be limited by factors such as activation of Calvin cycle enzymes and/or stomatal dynamics (Lawson and Blatt, 2014; Taylor and Long, 2017; Salter et al., 2019).

Stomata control CO2 and water vapor exchange between the leaf and the atmosphere, and thus play a unique role in crop productivity and yield (Lawson et al., 2010, 2012). Stomata respond to environmental changes by modifying pore aperture, and both internal and external signals are involved (Lawson and Blatt, 2014). Although external environmental stimuli (e.g., VPD, light, water availability, heat) often occur in combination, stomata generally open in response to high or increasing light intensity, low CO2 concentration [CO2] and low vapor pressure deficit (VPD), while stomata close in the opposite conditions (Outlaw, 2003; Lawson et al., 2014). In the field, leaf self-shading, cloud cover and sun angle often lead to rapid changes in photosynthetic photon flux density (PPFD), to which photosynthesis rapidly responds while stomatal responses are an order of magnitude slower (Lawson et al., 2010, 2012; Lawson and Blatt, 2014; Slattery et al., 2018). Slow stomatal responses can lead to (i) reduced A due to restricted CO2 diffusion during a low to high light transition, or (ii) unnecessary water loss during a high to low light transition when stomata lag behind decreases in A. Indeed, recent reports suggested that in wheat stomatal limitation of photosynthesis can be up to 10% (McAusland et al., 2016) leading to potential impacts on crop productivity (Lawson and Blatt, 2014; Taylor and Long, 2017; Vialet-Chabrand et al., 2017; Faralli et al., 2019; Vialet-Chabrand and Lawson, 2019). These findings highlight the advantage of selecting genotypes with fast stomatal responses to changes in irradiance, as rapid stomatal opening can increase photosynthetic rate whilst rapid stomatal closure can enhance water use efficiency at the crop level, leading to increased soil moisture conservation and therefore delay the onset of stress during periods of low rainfall (McAusland et al., 2016; Qu et al., 2016).

Although interspecific variation in stomatal responses to changes in light intensity have been previously reported (Vico et al., 2011; McAusland et al., 2016), to our knowledge there are no reports demonstrating intraspecific variation in the rapidity of stomatal responses in wheat. In addition, there are limited reports on the effects of developmental and environmental factors on stomatal rapidity (e.g., Leakey et al., 2002; Gerardin et al., 2018; Haworth et al., 2018). In particular, climate change has been associated with more frequent periods of water stress (Ray et al., 2012) and a significant increase in atmospheric [CO2] (Ainsworth and Rogers, 2007), two environmental conditions that strongly affect both A, and gs and therefore crop productivity. Therefore, the main aims of this work were, (i) to assess the extent of natural variation in the speed of stomatal responses in selected wheat cultivars; (ii) to determine the influence of developmental stage (late vegetative, booting, and post-anthesis stages) on such variation; and (iii) to evaluate the impact of reduced water availability and elevated atmospheric [CO2] on the rapidity of stomatal responses. A panel of eight winter wheat genotypes, capturing ∼80% of the United Kingdom single nucleotide polymorphism variability (Gardner et al., 2016), was phenotyped at different developmental stages for stomatal rapidity and photosynthetic capacity. In addition, a selected genotype was used to assess the impact reduced water availability and elevated [CO2] on stomatal kinetics.

## MATERIALS AND METHODS

#### Plant Material

Eight elite wheat varieties adapted to the United Kingdom were selected: Alchemy, Brompton, Claire, Hereward, Rialto, Robigus, Soissons, and Xi19. These are the founder lines of the 'NIAB Elite MAGIC' multi-parent advanced generation inter-cross (MAGIC) population (Mackay et al., 2014). Seeds were sown in plastic trays containing compost and germinated in a growth cabinet (Reftech BV, Sassenheim, Netherlands) at ∼200 µmol m−2 s −1 PPFD, 14 h/10 h photoperiod (light/dark), ∼15◦C on average and ∼60% relative humidity (RH). The compost material (Levington F2S) contained fertilizer (144 mg L−1 N, 73 mg L−1 P, 239 mg L−1 K, adjusted to pH 5.3–6.0 with dolomitic lime) and incorporated coir and sand. Plants were watered every 2 days. At BBCH (Biologische Bundesanstalt, Bundessortenamt und Chemische Industrie) growth stage (GS) 12 (GS12, two seedling leaves unfolded; Lancashire et al., 1991) seedlings were moved into a cold room for vernalization: 4◦C, ∼50 µmol m−2 s −1 PPFD

at 10 h/14 h photoperiod (light/dark) for 8 weeks. After vernalization, seedlings (one per pot) were transplanted into 1.5 L (15 cm diameter; 12 cm deep) or 4 L (16.5 cm diameter; 21 cm deep) pots (depending on the experiment) containing Levington F2S compost (Everris, Ipswich, United Kingdom). After which plants where transferred to either the glasshouse or controlled growth environment depending on experimental design (see below).

#### Growth Conditions and Experimental Design

#### Experiment 1: Phenotyping Stomatal Rapidity at Different Developmental Stages

To assess the presence of natural variation for stomatal rapidity and to determine the influence of developmental stage on this trait, plants were grown in a greenhouse in a fully randomized block design, in six blocks (n = 6). Solar radiation was supplemented with sodium vapor lamps (∼200 to 400 µmol m−2 s −1 . Hortilux Schreder 600W, Monster, Netherlands) and maintaining a 12 h photoperiod. Air temperature was on average ∼20◦C during the day and ∼15◦C at night. Water was applied daily to avoid soil moisture deficit, while full strength Hoagland's nutrients solution (∼100 mL per pot) was applied weekly. Owing to the different developmental pattern of the lines studied in this work, plants were visually scored for growth stage every 2 days. All phenotypic measurements were collected at BBCH GS25-31 (vegetative growth, tillering to start of stem extension), GS41-45 (early reproductive growth, booting stage) and GS71-75 (post-anthesis; 'watery ripe' to 'medium milk' stages of grain).

#### Experiment 2: Stomatal Rapidity Under Reduced Water Availability

To evaluate the impact of reduced water availability on stomatal dynamics, plants (cv. Soissons) were transplanted into 4 L pots and watered daily to avoid soil moisture deficit until the start of the treatment, and nutrients were supplied with Hoagland's solution (∼100 mL per pot, until the start of water availability manipulation). Between GS45 and GS51, pots were watered daily to ensure full soil water capacity by weighing the pots (∼3000 g of pot target weight). The non-stressed plants (well-watered, WW, n = 6) were watered daily throughout the experiment, whereas the progressive soil drying treatment was applied by removing watering to the water stressed plants (WS, n = 6). Water content in the pot was expressed as the fraction of transpirable soil water (FTSW). The FTSW method was recently summarized by King and Purcell (2017), and briefly described as follows: FTSW = (Pg – Pd)/TTSW, where (i) total transpirable soil water (TTSW) was the difference between the pot weights at 100% water holding capacity (WHC) (pot weight ∼3000 g including plant and plastic pot) and when transpiration rate of the stressed plants decreased to 10% of the control plants, (ii) Pg was the actual pot weight on a given date, and (iii) Pd was the pot weight at the time when transpiration rate of stressed plants was 10% of the control plants (∼1300 g of pot weight). Gas exchange analyses were carried out when FTSW was ∼0.2–0.3 for WS plants, and ∼0.8–0.9 for the WW treatment. The value at which WS plants were analyzed was chosen to represent a soil water stress condition at which wheat has previously been found to show typical stress symptoms (e.g., significant reduction of gs , leaf water potential and leaf relative water content) (Weldearegay et al., 2016). Two sets of soil drying treatments where carried out separately (n = 3 for WS for each cycle) to avoid overlaps between replicates during the phenotypic analysis (**Supplementary Figure 1**).

#### Experiment 3: Stomatal Rapidity Under Elevated Atmospheric [CO2]

To evaluate the impact of elevated atmospheric [CO2] on the rapidity of stomatal responses a third experiment was carried out in growth chambers in which atmospheric [CO2] was manipulated (Conviron Adaptis A1000, Conviron, Canada). Plants (cv. Soissons) were transplanted into in 1.5 L pots (one per pot) and placed into two growth chambers, one set of pots (n = 6) at ambient [CO2] ([CO2] 446 ± 31 µmol mol−1 on average) and the other (n = 6) at elevated [CO2] (706 ± 6 µmol mol−1 on average) (**Supplementary Figure 2**). The light level inside both chambers at leaf height was ∼400–800 µmol m−2 s −1 with a 12 h photoperiod. Air temperature was maintained at ∼20◦C through the day and ∼15◦C at night, and RH maintained at ∼60%. Plants were watered every 2 days with Hoagland's solution (∼100 mL per pot). Phenotypic analyses were carried out at GS25-31 (33–42 days after sowing) as described below (**Supplementary Figure 2**).

#### Phenotypic Analysis

#### Analyses of the Rapidity of gs to Changes in Light Intensity

In each experiment, the third fully expanded leaf at GS31, and the flag leaf at GS41 and GS71 were tagged on each plant at the onset of each selected growth stage. Prior to gas exchange analysis, plants were transferred from the greenhouse to a temperature and humidity-controlled room (∼20◦C temperature and ∼60% RH) and gas exchange measurements performed on the middle of the leaf lamina using an open infrared gas exchange system fitted with a 2 cm2 leaf cuvette and integral blue–red LED light source (LI-6400–40; LI-COR, Lincoln, NE, United States). All measurements were collected between 8:30 and 15:00 and randomized to avoid any potential diurnal influence over a 8 week measurement period. Prior to measurement, leaves were first equilibrated at a PPFD of 100 µmol m−2 s −1 until both A and gs reached 'steady state,' defined as a ∼2% maximum change in rate during a 10 min period (generally 60 min). After equilibration, PPFD was increased to 1500 µmol m−2 s −1 for 1 h, and subsequently returned to 100 µmol m−2 s −1 for 1 h. The conditions inside the leaf cuvette were kept constant at 20 ± 0.1◦C leaf temperature, at VPD of 1 kPa with a dew point generator (LI-610; LI-COR, Lincoln, NE, United States) and at 400 µmol CO2 mol−1 air (ambient CO2 concentration, Ca). In Experiment 3 the plants grown at ∼700 µmol mol−1 [CO2] were analyzed at 700 µmol mol−1 Ca. Values were logged every minute throughout the three h measurement cycle. Intrinsic water use efficiency (iWUE) was

calculated as iWUE = A/gs . All data were analyzed according to the exponential model of Vialet-Chabrand et al. (2013) as described in McAusland et al. (2016). Variables estimated with the exponential model were steady-state photosynthesis at saturating light (A), steady state stomatal conductance at saturating light (gs), Ki (time constant for rapidity of stomatal opening), Kd (time constant for rapidity of stomatal closing) and 'time to reach 95% A' (T95%A) (**Figures 1A,B**). The limitation of A by gs (gslimitA) was calculated by estimating a hypothetical A if no stomatal limitation was present (McAusland et al., 2016) and determining the differences with the measured kinetic values. The 'time to restore iWUE' (TiWUE) was defined as the time necessary to recover the maximum iWUE value during the high to low light transition. TiWUE was calculated

FIGURE 1 | Example of a step-change in light for the flag leaf of a wheat plant (cv. Soissons), collected with a Li-Cor 6400 at GS41. (A) Step-change from low to high light (100 to 1500 µmol m−2 s −1 PPFD), and (B) step-change from high to low light (1500 to 100 µmol m−2 s −1 PPFD). In (A), black dots represent CO2 assimilation rate (A), whereas white dots represent stomatal conductance (gs). In (B), white dots represent stomatal conductance (gs) while gray dots represent intrinsic water-use efficiency (iWUE) calculated as iWUE = A/gs. White areas represent 1500 µmol m−2 s −1 PPFD, gray areas 100 µmol m−2 s −1 PPFD. Estimated variables with the exponential model described by Vialet-Chabrand et al. (2013) are Ki (time constant for rapidity of stomatal opening), Kd (time constant for rapidity of stomatal closing) and time to reach 95% A (T95%A.) The limitation of A by gs (gslimitA) was estimated by assuming a hypothetical A if no stomatal limitation was present immediately after a low to high light transition (McAusland et al., 2016). Time to restore iWUE (TiWUE ) was calculated with segmented regression, and estimated as the intercept between the two linear segments. The gs at the two iWUE intercepts were used to calculate the limitation of iWUE by gs (gslimitiWUE) by assuming an instantaneous stomatal closure after a high to low light transition.

using segmented regression and estimated as the intersection between the two linear segments (**Figure 1B**). The gs at the point of intercept was used to determine the 'limitation of iWUE by gs ' (gslimitiWUE) by calculating the integrated difference with measured values following the high to low light transition (**Figure 1B**).

#### A/Ci Curves

Photosynthesis measurements (A/Ci curves) were performed between 9:00 and 12:00 on the fully emerged flag leaf at GS41-45 in Experiment 1. Measurements of the response of A to sub-stomatal CO2 concentrations (Ci) were performed in the middle of the tagged leaf using an open infrared gas exchange system and a 2 cm2 leaf cuvette with an integral blue–red LED light source (LI-6400–40; LI-COR, Lincoln, NE, United States). In the cuvette, PPFD was maintained at a saturating level of 1500 µmol m−2 s −1 , a leaf temperature of 20 ± 0.1◦C, a VPD between 0.9 and 1.3 kPa and a Ca of 400 µmol mol−1 . When steady-state conditions were achieved, Ca was sequentially decreased to 300, 200, 100, and 75 µmol mol−1 before returning to the initial concentration of 400 µmol mol−1 . This was followed by a sequential increase to 550, 700, 1000, and 1200 µmol mol−1 . Readings were recorded when A had stabilized to the new conditions. The maximum velocity of Rubisco for carboxylation (Vcmax) and the maximum rate of electron transport demand for Ribulose 1,5-bisphosphate (RuBP) regeneration (Jmax) were derived by curve fitting, as described by Sharkey et al. (2007).

#### Stomatal Density Analysis

At GS41-45 in Experiment 1, stomatal impressions were collected at the same point of the leaf lamina used for gas exchange analyses, on both the adaxial (n = 6) and abaxial (n = 6) side of the leaf. A negative impression was made using a dental polymer (Xantoprene, Heraesus Kulzer, Ltd., Hanau, Germany) (Weyers and Johansen, 1985). After the material had dried, a positive impression was produced using nail polish on a microscope slide. Stomatal density and pore length were determined using a light microscope by averaging the value of six fields of view for each leaf with a size of ∼1250 µm2 captured from each impression and using a 5 MP eye-piece camera (MicroCAM 5 MP, Bresser Optics, Rhede, Germany).

#### Statistical Analysis

Statistical analyses were conducted using SPSS (v.16; SPSS, Inc., Chicago, IL, United States) and R1 . A two-way analysis of variance (ANOVA) was used for gas exchange data when two factors (genotype × growth stage) were present (i.e., for the variables A, gs , Ki , Kd, T95%A, gslimitA, TiWUE for Experiment 1). Single factor analyses were carried out using one-way ANOVA (i.e., for A, gs , Ki , Kd in Experiments 2 and 3). Shapiro–Wilk and Levene's tests were used to test data for normality and homogeneity of variance, respectively. Duncan's test was used for multiple comparisons. When present, linear curves were fitted with

1http://www.r-project.org/

major axis regression thus minimizing the variability for the traits of interest in both the axes. The strength of trait associations at GS41-45 (between steady-state and dynamic gas exchange, anatomical and photosynthetic capacity traits) and for all developmental stages (between steady-state and dynamic gas exchange traits) were measured using Pearson's correlation coefficient.

#### RESULTS

#### Speed of Stomatal Responses at Different Developmental Stages

Significant genotypic variation (P < 0.001) in steady-state A and gs at 1500 µmol m−2 s −1 was recorded for the eight wheat cultivars investigated (**Figures 2A–F**). Soissons and Xi19 showed the highest A and gs values, whereas Hereward showed consistently lower values. There was a significant effect of growth stage on A and gs (P < 0.001 for both), with most of the cultivars showing higher values at GS41. Significant variation in the time constants for stomatal opening (Ki) was recorded between cultivars (P = 0.038) (**Figures 2G–I**) and developmental stage significant impact Ki (P < 0.001) in the majority of cultivars, with a lower time constant (thus faster gs responses) at GS31 and GS41 compared with GS71. However, in cultivars Claire, Rialto and Robigus, there was no significant effect of growth stage on Ki . Similarly, Kd varied significantly between the different growth stages (P < 0.001), although no significant genotypic differences were found (P = 0.343) (**Figures 2J–L**). Most of the cultivars achieved 95% A between 7 and 15 min following a step increase in light intensity when analyzed at GS31 and GS41 and significant variation (P = 0.045) existed between cultivars (**Figures 2M–O**). At GS71, T95%A was significantly longer than GS31 and GS41 (P < 0.001), between 14 and 25 min.

When plants were subjected to a step increase in light intensity, photosynthesis was limited by the slow increase in gs , with an average limitation (gslimitA) between 7 and 15% across genotypes (P = 0.019) and growth stages (**Figures 3A– C**). Soissons and Alchemy showed the greatest limitation of A by gs (∼12% on average) while, Rialto, Hereward and Claire were less limited at ∼8% on average. Generally, gslimitA was exacerbated at GS71 (P < 0.001), although some genotypes (Claire, Rialto) did not show any significant increases in gslimitA at GS71 compared to GS41.

The time to restore iWUE (TiWUE) was generally faster at GS31 compared to GS41 and GS71 (P < 0.001) (**Figures 4A– C**). Hereward was the quickest to restore iWUE due to fast stomatal closure (low Kd) at GS31 and GS41, whilst the slowest responses were observed in Alchemy at GS31 and Soissons at both GS41 and GS71 (P = 0.014). gslimitiWUE was significantly different between cultivars (P = 0.030) and growth stages (P < 0.001) (**Figures 4D–F**). Across all of the growth stages measured, the temporal response of gs for opening and closing were significantly correlated with T95%A and gslimitA (**Figure 5**). At the same time, significant correlations were found between TiWUE and the time constant for stomatal closing.

## Photosynthetic Capacity at Flag Leaf Stage

Significant genotypic variation in Vcmax (P < 0.024) was observed within the eight cultivars analyzed (**Figures 6A,B**). Rialto, Soissons, and Xi19 showed the highest values for both Vcmax and Jmax (∼160 and 260 µmol m−2 s −1 on average, respectively) whereas Robigus and Hereward displayed the lowest values. Significant positive correlations were observed between photosynthetic capacity traits (A, Vcmax, Jmax), gs , speed of stomatal responses and stomatal density (**Figure 7**). A significant positive relationships was observed between gs and A whilst a negative relationship between gs and iWUE was recorded. In addition, A was significantly and positively correlated with most of the stomatal kinetics related traits (Ki , Kd, T95%A, gslimitA). Interestingly, iWUE positively correlated with the gslimitA. Significant and positive correlations were found between the gslimitA, T95%A, and Ki .

### Stomatal Anatomical Features at Flag Leaf Stage

Stomatal density and pore length were significantly different between the cultivars (P = 0.002 for abaxial and P < 0.001 for adaxial stomatal density while P = 0.013 for abaxial and P = 0.001 for adaxial pore length) (**Table 1**). The abaxial density ranged from 63.7 to 81.6 stomata mm−2 while the adaxial density was between 61.0 and 90.4 mm−2 . Stomatal density was correlated with Ki (adaxial, positive) and T95%A (abaxial, negative) (**Figure 7**) while abaxial pore length was negatively correlated with abaxial stomatal density (**Figure 7**).

### Speed of Stomatal Responses Under Reduced Water Availability

Using the variety Soissons, reduced water availability significantly reduced A and gs at 1500 µmol m−2 s −1 PPFD by 45 and 63% respectively (P < 0.001) (**Figures 8A,B**). The time constant Ki was increased (P = 0.036) in plants grown under water stress (WS) conditions compared to the well-watered controls (WW) (**Figure 8C**). In contrast, a significantly lower Kd (P = 0.022) was recorded under WS compared with WW (**Figure 8D**).

## Speed of Stomatal Responses Under Elevated [CO2]

The cv. Soissons grown under 700 µmol mol−1 [CO2] showed a 25% increase in A compared to the rate in control plants grown at 400 µmol mol−1 [CO2] (**Figure 8E**). In contrast, a small reduction in gs (6%) was recorded under elevated [CO2], although this was not significantly different from gs at 400 µmol mol−1 [CO2] (**Figure 8F**). Elevated [CO2] significantly reduced Ki (P = 0.047), while no differences were found for Kd (**Figures 8G,H**).

## DISCUSSION

### Genotypic Variation for Stomatal Rapidity in Wheat

Previous work has demonstrated the presence of significant interspecific (Vico et al., 2011; McAusland et al., 2016) and intraspecific (e.g., rice, Qu et al., 2016) variation in the rapidity of stomatal responses or photosynthetic induction (Salter et al., 2019) in crops. Here, we show that significant genotypic variation in the rapidity of gs is present in wheat in response to step changes in irradiance. Consistent with the conclusions of previous work (e.g., Vico et al., 2011; Lawson et al., 2012; McAusland et al., 2016), the time to reach maximum steady state gs ranged from 7 to 27 min between cultivars. Cultivars with faster gs opening responses (lower Ki) (e.g., Hereward, Claire) achieved 95% A more rapidly than those cultivars with slower gs kinetics (e.g., Xi19, Soissons) supported by the positive correlation between Ki and T95%A. At the same time, cultivars with faster stomatal closing (lower Kd, e.g., Hereward and Claire at GS41) following a high to low light transition achieve a

FIGURE 5 | Relationships between the estimated parameters for stomatal opening and closing for all eight wheat varieties at all the growth stages analyzed. Data points are means (n = 4–7) for the eight cultivars at three different growth stages. Correlation coefficients between parameters are shown in the top right panels. In the bottom panels, regression was fitted using major axis regression. Fitting lines are shown only when the correlation is significant (P < 0.05).

FIGURE 7 | Correlation matrix including the correlation coefficient between parameters describing the temporal response of gs during opening and closing, photosynthetic capacity and anatomical features for stomata of the flag leaf of wheat plants at GS41. In the bottom panels, regression was fitted by using major axis regression. Fitting line is shown only when the correlation was significant (P < 0.05).

higher iWUE, more rapidly. These findings support previous reports in which the 'speedy stomata' trait has been considered a potential target for maximizing CO2 diffusion and A, as well as iWUE, particularly under dynamic light regimes (Lawson and Vialet-Chabrand, 2018). Significant differences in stomatal density and pore length were also observed between cultivars; interestingly, the variation in stomatal density was greater on the adaxial than the abaxial surface. However, only a weak correlation between stomatal density (adaxial) and Ki was apparent, indicating minimal anatomical influence on the speeds of gs response in the panel of wheat cultivars analyzed. Additionally, our findings are contrary to previous research on the relationship between stomatal speed and density in the non-domesticated species of the dicot genus Banksia that have reported higher stomatal density results in faster responses (Drake et al., 2013).

In rice (Qu et al., 2016) and other species (McAusland et al., 2016), asymmetric stomatal responses (e.g., faster stomatal closure that opening) have been suggested as a strategy of prioritizing water conservation over CO2 uptake. In our work, the relatively conserved ratio of Ki :Kd (at all growth stages) in all the cultivars studied indicates a balance between carbon gain and water conservation. However, although the time constant for opening and closure were comparable, the fact that TiWUE was significantly higher than T95%A indicates that slow gs responses had a greater impact on iWUE than A. While the varieties studied in this work are adapted to a north–west European environment (Mackay et al., 2014), and therefore likely optimized for carbon gain rather than iWUE, wheat cultivars adapted to lower rainfall regimes may provide a more extensive natural diversity for water conservation (i.e., faster stomatal closure rather than opening). To our knowledge, this is the first report demonstrating natural variation in the speed of stomatal responses in wheat at the leaf level. However, new cutting-edge technologies, for example whole plant gas-exchange (Jauregui et al., 2018), would enable the impact of the speed of stomatal responses on whole plant net carbon assimilation and water use to be evaluated. Cultivars with fast gs responses (e.g., Claire, Robigus, and Hereward) were followed by lower A and gs values thus showing potential elevated adaptation to dynamic light environment and potentially water deficit conditions. In contrast, Soissons and Xi19 demonstrated high overall gs values, but slow gs responses, traits that may be useful for environments in which light is high and constant with higher temperatures but with sufficient water to support high gs and evaporative cooling. These data suggest that phenotyping wheat lines for stomatal rapidity has the potential to identify novel targets for improving wheat productivity for exploitation in breeding programs.

### Photosynthetic Capacity and Speed of Stomatal Responses

In our study, a significant variation for Vcmax and steadystate A and gs was found between cultivars, consistent with previous studies in wheat (e.g., Driever et al., 2014; Gaju et al., 2016). However, cultivars with greater gs rapidity displayed lower photosynthetic capacity demonstrated by the positive relationship between A and gs with T95%A, and the time constants for stomatal opening and closing (Ki and Kd), respectively. This suggests a compromise between the rapidity of stomatal behavior and the values of steady state A and gs achieved. Stomatal movement involves a series of hierarchical processes based on the transport, accumulation, and release of osmotically active solutes (Lawson and Blatt, 2014) as well as subsidiary cell physiology (Raissig et al., 2017), and any variation in these processes could result in differences in stomatal behavior. For

example, variation in vascular connectivity (e.g., vein density) could explain the positive relationship between steady state A and gs and the speed of gs . Feldman et al. (2017) recently showed stronger photosynthetic performance in rice with increased leaf vein densities via mutagenesis. It is therefore conceivable that concurrent improvements for stomatal rapidity, photosynthetic capacity and for maximum A and gs could be attained if vein density and hydraulic efficiency were improved.

### Leaf Age Affects the Rapidity of gs in Wheat

A novel finding of this work is the significant effect of growth stage on stomatal responses. The rapidity of gs was reduced at post-anthesis stage (GS71) compared to the earlier developmental stages (GS31 and GS41) and this corresponded with a significant decrease in both steady-state A and gs . The decrease in post-anthesis photosynthetic capacity, and therefore reduction in radiation use-efficiency in cereals, has been reported previously (Bingham et al., 2007; Carmo-Silva et al., 2017), and mainly attributed to the onset of leaf senescence (Gaju et al., 2016). The activation of the senescence signaling pathway, thought to be triggered by sink feedback (e.g., Bingham et al., 2007), leads to degradation of chlorophyll and Rubisco and subsequent re-allocation of nutrients from the senescing parts (i.e., leaves) to the growing sink (i.e., grain), thus leading to reduction in the efficiency of the source (Camargo et al., 2016).

Data were analyzed by using one-way ANOVA and different letters represent significant differences according to Duncan's test.

However, to our knowledge, this is the first report showing developmental effects on stomatal responses to changes in light intensity. In particular, the data highlight growth stageand genotype-dependent variation in stomatal rapidity, and the importance of taking into account these variables when quantifying dynamic stomatal traits. Additionally, periods of low precipitation and/or high temperature are more common during the post-anthesis stage, often leading to significant

yield reductions. Faster stomatal opening could facilitate greater utilization of sudden increases in irradiance, and thus not only provide more assimilates for grain filling, but avoid any potential damage from excess excitation pressure (Yamasaki et al., 2002). Increased A is particularly important in view of the potential source-limitation (or at least source-sink colimitation), which has been reported during grain filling in several wheat cultivars (Álvaro et al., 2008; Acreche and Slafer, 2009). Additionally, as wheat is extremely sensitive to temperature (Yamasaki et al., 2002) rapid gs responses to increasing irradiance will facilitate maintenance of nearer optimal leaf temperatures to support maximum photosynthetic performance (Lawson and Vialet-Chabrand, 2018).

On the other hand, water conservation strategies would be enhanced by faster stomatal closure when carbon gain is reduced (e.g., during high to low light transition), thus improving the water-use budget and helping to reduce early soil water exhaustion (Bodner et al., 2015). For example, Hereward, Claire, and Robigus showed very quick gs responses overall with minimal developmental effects (apart from Hereward at GS71), thus being good candidates for breeding exploitation for stomatal rapidity. The fact that a significant variation was observed for Ki , as well as a stage × genotype interaction for Kd and TiWUE, suggests that the targeted exploitation of existing natural variation could be used to facilitate carbon gain for photosynthesis and optimize wateruse under dynamic field environments and at different stages of wheat development.

## Water Stress and Elevated CO2 Concentration Affects Stomatal Rapidity

The effect of elevated [CO2] and water stress on stomatal rapidity has received little attention to date. A recent report on Arundo donax (Haworth et al., 2018), showed that water stress increases the rapidity of stomatal closure and reduced the speed of opening, consistent with our data in wheat. Similarly, in Lawson and Blatt (2014), Vicia faba plants subjected to water stress showed a faster gs reduction during a shade fleck whilst a slower gs increase was recorded for a sun fleck. However, recent work by Gerardin et al. (2018) reported an increase in rapidity for both the opening and the closing phase in Nicotiana tabacum under reduced water availability. It should be noted that in N. tabacum a strong asymmetry between the opening and closing phase (due to a faster closing phase) under control conditions was also reported. Under optimal soil water availability, asymmetric stomatal responses have not been previously described in wheat (e.g., McAusland et al., 2016), thus suggesting that the opening/closing ratio under optimal growth conditions might be species-specific and strongly influenced by water status. Thus, the presence of asymmetric stomatal responses under stress conditions could be considered as: (1) an adaptation to reduce water loss (stronger coordination between A and gs) and (2) a mechanism to limit increasing gs after steady state A has been achieved (McAusland et al., 2016). Our data suggests that both possibilities are conceivable under reduced water availability, with both high Ki and low Kd values observed in wheat. Water stress therefore exacerbates conservative responses under dynamic light in wheat allowing further opportunities for adaptation to reduced water availability conditions.

Only a handful of studies have examined the effect of atmospheric [CO2] on stomatal kinetics, with most research focusing on the effects for steady stage gs or changes in stomatal anatomy (Ainsworth and Rogers, 2007). Leakey et al. (2002) reported that in Shorea leprosula, the relative enhancement of biomass driven by elevated [CO2] was greater under dynamic irradiance compared to uniform irradiance. Consistent with our findings in wheat, Leakey et al. (2002) suggested that faster stomatal opening under dynamic conditions reduced the time to reach maximum gs and reduced CO2 limitation of A. Therefore, a faster stomatal opening phase (in response to an increase in irradiance) might be a leaf trait that has an additional positive effect under elevated [CO2] that deserves further investigation at the field level. Further efforts should focus on understanding and quantifying the effects of these major environmental factors on stomatal dynamics under fluctuating light environments.

## CONCLUSION

To our knowledge, this is the first report showing significant genotypic variation in wheat for the rapidity of stomatal responses. Our work illustrates that slow gs responses can limit A during a low to high light transition by 7–15%, while slow reduction of gs during a high to low light transition strongly limits water conservation. Measurements obtained post-anthesis suggest that leaf age might exacerbate stomatal limitations by reducing the rapidity of stomatal responses, whilst environmental cues (i.e., water stress and [CO2]) also affected this. Evidence of significant genotypic variation for these traits highlights them as novel and as yet unexploited targets for crop improvement programs, which aim to develop cultivars that maximize photosynthesis and minimize the waste of water in the dynamic light environments encountered in the field. This work lends to a greater understanding of the interactions between stomatal behavior, environmental cues and leaf performance, which guides the establishment of ideotypes for specific growth environments. For example, the cultivar Hereward demonstrated fast gs responses at GS 31 and 41 and minimal limitation of A, with potential for exploitation to provide ideotypes for environments in which conservation of water use is a priority. On the other hand, cultivars such as Soissons and Xi19 demonstrated high photosynthetic capacity, high overall gs values, but slow gs responses, traits that may be useful for high-light and high-temperature environments. Improvement of stomatal responses under a dynamic light environment might support the optimization of resource use and yield in major crops, and therefore inform the development of new crop ideotypes with higher yield potential and resilience to future environmental changes.

### AUTHOR CONTRIBUTIONS

MF and TL design the experiments, analyzed the data, and wrote the manuscript. MF executed all the experiments and acquired

all the data. SW analyzed stomatal density and pore length. JC, EO, AG, CR, and JVR helped with interpretation of data and edit the manuscript. TL, JC, EO, and CR acquired project funding and resources.

#### FUNDING

MF was supported by Biotechnology and Biological Sciences Research Council (BBSRC) grants to TL (BB/NO16831/1) and JC (BB/N01698X/1), with IPA co-funding from BASF. SW was supported through a BBSRC Industrial Studentship (1775930) award to BASF (JVR), Essex (TL), and NAIB (JC). Dr.

#### REFERENCES

Silvère Vialet-Chabrand was acknowledged for the development of the R scripts.

#### SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2019.00492/ full#supplementary-material

TABLE S1 | Duncan's multiple comparisons test output carried out for the gas-exchange data in Experiment 1. The test was performed on both "cultivar" and "stage" factors. In the analysis of the factor "stage", vegetative, flag, and heading represents GS31, 41, and 71 respectively.

and nitrogen-use efficiency in landraces, synthetic-derived lines and cultivars in wheat. Field Crop. Res. 193, 1–15. doi: 10.1016/j.fcr.2016.04.018

photosynthesis and water-use efficiency. New Phytol. 211, 1209–1220. doi: 10. 1111/nph.14000

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Copyright © 2019 Faralli, Cockram, Ober, Wall, Galle, Van Rie, Raines and Lawson. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# Impact of Stomatal Density and Morphology on Water-Use Efficiency in a Changing World

*Lígia T. Bertolino1,2 , Robert S. Caine2 and Julie E. Gray2 \**

*1Grantham Centre for Sustainable Futures, University of Sheffield, Sheffield, United Kingdom, 2Department of Molecular Biology and Biotechnology, University of Sheffield, Sheffield, United Kingdom*

Global warming and associated precipitation changes will negatively impact on many agricultural ecosystems. Major food production areas are expected to experience reduced water availability and increased frequency of drought over the coming decades. In affected areas, this is expected to reduce the production of important food crops including wheat, rice, and maize. The development of crop varieties able to sustain or improve yields with less water input is, therefore, a priority for crop research. Almost all water used for plant growth is lost to the atmosphere by transpiration through stomatal pores on the leaf epidermis. By altering stomatal pore apertures, plants are able to optimize their CO2 uptake for photosynthesis while minimizing water loss. Over longer periods, stomatal development may also be adjusted, with stomatal size and density being adapted to suit the prevailing conditions. Several approaches to improve drought tolerance and water-use efficiency through the modification of stomatal traits have been tested in the model plant *Arabidopsis thaliana*. However, there is surprisingly little known about the stomata of crop species. Here, we review the current understanding of how stomatal number and morphology are involved in regulating water-use efficiency. Moreover, we discuss the potential and limitations of manipulating stomatal development to increase drought tolerance and to reduce water loss in crops as the climate changes.

#### *Edited by:*

*Michael Vincent Mickelbart, Purdue University, United States*

#### *Reviewed by:*

*Fulai Liu, University of Copenhagen, Denmark Jeroni Galmes, Universitat de les Illes Balears, Spain*

> *\*Correspondence: Julie E. Gray<EMAIL_ADDRESS>
#### *Specialty section:*

*This article was submitted to Plant Physiology, a section of the journal Frontiers in Plant Science*

*Received: 28 September 2018 Accepted: 11 February 2019 Published: 06 March 2019*

#### *Citation:*

*Bertolino LT, Caine RS and Gray JE (2019) Impact of Stomatal Density and Morphology on Water-Use Efficiency in a Changing World. Front. Plant Sci. 10:225. doi: 10.3389/fpls.2019.00225*

Keywords: water-use efficiency, stomatal conductance, stomatal density and size, drought response, crops

## INTRODUCTION

Changes in climate are already negatively affecting the yields of staple crops in agricultural areas around the world (Lobell et al., 2011; IPCC, 2014). As the globe continues to warm, changes in the hydrological cycles are, in general, increasing aridity and the incidence of droughts (Dai, 2013; Sherwood and Fu, 2014). Agriculture will need to adapt quickly to ensure that water is used more efficiently, while maintaining food security in a world where human population is rapidly growing. Sustainable and climate-smart management of water, land, and biodiversity will be important for achieving these objectives (discussed in Howden et al., 2007; Campbell et al., 2014; Lipper et al., 2014; Iglesias and Garrote, 2015). Moreover, the development of crop varieties that have improved water-use efficiency (WUE) under predicted future climates will also be critical (Flexas, 2016; Varshney et al., 2018). WUE can be estimated at different scales; at an agronomic level, it is described as the ratio of water used in crop production versus biomass or yield (Condon et al., 2004; Medrano et al., 2015). From a plant physiology point of view, and as it will be primarily addressed here, WUE is the amount of CO2 fixed in photosynthesis (*A*) relative to the amount of water vapor lost to the atmosphere (Willmer and Fricker, 1996; Condon et al., 2004; Bacon, 2004). As stomata play a fundamental role in regulating plant water use and carbon gain, they present a key target for improving WUE. Here, we review how changes in stomatal developmental traits can affect plant WUE and also drought tolerance.

Stomata are microscopic structures consisting of a pair of specialized guard cells that surround a central pore. They are found on aerial surfaces of most plants, providing access to mesophyll cells (Zeiger et al., 1987; Hetherington and Woodward, 2003). By actively adjusting guard cell turgor pressure, plants can alter stomatal pore aperture, thereby moderating gas exchange rates between the leaf interior and the atmosphere (Zeiger et al., 1987; Kollist et al., 2014). Increases in guard cell turgor pressure lead to a greater stomatal pore aperture, which enhances the rates of CO2 uptake for *A* and of water loss, *via* a process termed stomatal conductance (*gs*) (Condon et al., 2002; Hetherington and Woodward, 2003). On the other hand, reductions in guard cell turgor pressure lead to decreases in stomatal aperture and in *gs*. The signals governing the fluxes of CO2 and water to and from the plant mesophyll are highly coordinated, allowing plants to finely balance the need for carbon with the need to moderate water loss (Wong et al., 1979; Haworth et al., 2016; Sorrentino et al., 2016). This internal crosstalk is influenced by many environmental factors, including changes in temperature, light intensity, atmospheric CO2 concentration, air humidity, and soil moisture content (Farquhar and Sharkey, 1982; Schroeder et al., 2001; Mott, 2009; Assmann and Jegla, 2016; Chaves et al., 2016). For example, when water becomes limited, signals such as reduced hydraulic conductivity and increased abscisic acid (ABA) arise, causing guard cell turgor pressure decreases, which result in reduced stomatal aperture and *gs* (Schroeder et al., 2001; Mustilli, 2002; Tombesi et al., 2015; Bartlett et al., 2016; McAdam et al., 2016). These changes lead to an improved water conservation, but often at the expense of *A* (Flexas and Medrano, 2002). Conversely, when water is plentiful in the soil or air, guard cell turgor increases, leading to increases in stomatal pore aperture and in *gs*, with *A* also often increasing.

Over longer periods, external signals perceived by mature leaves can also lead to systemic responses that moderate stomatal development on the new leaf epidermis, resulting in changes in stomatal patterning (Casson and Gray, 2008; Casson et al., 2010; Pillitteri and Torii, 2012; Chater et al., 2014; Qi and Torii, 2018).

FIGURE 1 | Stomatal traits vary between species. The eudicots (A) *Arabidopsis thaliana* and (B) *Phaseolus vulgaris* display kidney-shaped guard cells (colored in green). The grasses (C) *Oryza sativa* and (D) *Triticum aestivum* show dumbbell-shaped guard cells (solid green) and specialized subsidiary cells (light green gradient). Clear differences in stomatal size and stomatal density can be observed. Scale bars 10 μM.

Exposure of mature leaves to high CO2 or low light levels, for example, is known to cause reductions in stomatal density (*SD,* number of stomata per unit of area) and in stomatal index (*SI*, ratio of stomata to epidermal cells plus stomata, multiplied by 100) of new developing leaves (Lake et al., 2001; Miyazawa et al., 2006). Conversely, low CO2 and high light generally have the opposite effect. The impact of water availability on stomatal development is less understood, with mixed responses and differences among species being reported (Clifford et al., 1995; Xu and Zhou, 2008; Doheny-Adams et al., 2012; Sun et al., 2014; Zhao et al., 2015). In Arabidopsis, plants grown under water restriction do not show altered *SD*; however, reductions in stomatal size (*SS*, guard cell area, based on guard cell pair length and width) were observed (Doheny-Adams et al., 2012). These plastic modulations of number and size of stomata allow plants to adjust their stomatal pore area in response to the surrounding environment, ultimately affecting their maximum and minimum gas exchange.

Stomata exhibit a diverse range of shapes, sizes, and numbers across different plant species (**Figure 1**). There are profound differences in how the stomata of different groups develop and are patterned on the epidermis (Sack, 1994; Caine et al., 2016; Raissig et al., 2016; Rudall et al., 2017). Morphological differences include *SD*, *SS*, guard cell shape, and presence or absence of subsidiary cells. All of these parameters have the potential to influence stomatal movement and, consequently, plant *A*, *gs*, and WUE. Over evolutionary time, various stomatal traits have altered, potentially aiding in adapting plant species to new environments (Taylor et al., 2012; Drake et al., 2013; Haworth et al., 2018). Eudicots, for example, typically have kidney-shaped stomata that are formed on the leaf epidermis without a pre-determined location (MacAlister et al., 2007; Pillitteri and Dong, 2013). While in monocots, stomata can either be kidney-shaped or, as with the grasses, be composed of dumbbell-shaped stomata with neighboring subsidiary cells, collectively termed a stomatal complex (Rudall et al., 2017). In grasses, stomatal development is constrained to the leaf base, with stomatal pores being formed in specified cell files adjacent to veins (Stebbins and Shah, 1960; Rudall et al., 2013; Hepworth et al., 2018).

Although stomatal behavior, patterning and morphology are important factors that contribute to WUE (Lawson and Blatt, 2014; Lawson and Vialet-Chabrand, 2019), relatively little is known about how targeted modifications of stomatal traits affect physiological responses in crop plants, especially in field experiments. Efforts to improve WUE have often led to decreases in yield (Flexas, 2016). By attempting to alter stomatal features to improve water conservation, reductions in *gs* may arise, potentially leading to detrimental effects on *A*, evaporative cooling, and plant fertility. However, recent findings suggest that under at least some greenhouse and controlled environment growth conditions, changing stomatal traits may improve WUE without such undesirable yield penalties (Yu et al., 2013; Hughes et al., 2017; Caine et al., 2019). While these studies are encouraging, they offer only a snapshot of how plants with modifications in stomatal features might perform. Here, we discuss our current understanding of how alterations in *SS*, *SD,* and stomatal morphology contribute to altered WUE and drought tolerance with particular emphasis on the latest advances in crop species.

## VARIATION IN *SS* AND *SD* INFLUENCES GASEOUS EXCHANGE AND WUE

Dynamic adjustments to the opening degree of stomatal pores are responsible for regulating *gs* in the short term, allowing plants to quickly reduce water loss according to external cues (Farquhar and Sharkey, 1982). Over a longer term, anatomical adjustments, such as changes to *SS* and *SD*, can modify the range of *gs* by altering the maximum stomatal conductance (g*smax*) (Franks et al., 2009; Dow et al., 2014a). *Gsmax* refers to the maximal potential gas exchange in a state where all stomata are fully open. It is a theoretical estimate that is calculated using empirical stomatal anatomical measurements, including *SD*, stomatal pore depth (estimated as guard cell width), and maximum stomatal pore area (calculated based on pore length) (Franks and Beerling, 2009; Dow and Bergmann, 2014; Sack and Buckley, 2016). Despite operating *gs* normally being significantly lower than its maximum capacity (Fanourakis et al., 2015; McElwain et al., 2016), measured *gs* positively correlates with calculated *gsmax* (Franks et al., 2009). Furthermore, it is suggested that adaptations in *gsmax* allow plants to adjust their operating gas exchange rates while maintaining guard cells turgor pressure in an optimum state. This is believed to provide better stomatal sensitivity and rapid adjustment of aperture response (Franks et al., 2012; Dow and Bergmann, 2014). Therefore, although *SS* and *SD* are not the only variables determining leaf gas exchange, changes to these stomatal traits do permit plants to adjust both *A* and water use (Franks et al., 2009; Franks and Beerling, 2009; de Boer et al., 2011; Dow et al., 2014a).

Variation in size and density of stomata may arise due to genetic factors and/or growth under different environmental conditions. A negative correlation has frequently been suggested between these two stomatal traits. This inverse relationship has been observed in plastic developmental responses to changes in environment and also during long-term evolutionary adaptation (Dilcher et al., 2000; Ohsumi et al., 2007; Franks et al., 2009, 2012; Franks and Beerling, 2009; Doheny-Adams et al., 2012; Taylor et al., 2012; Sun et al., 2014; Fanourakis et al., 2015; de Boer et al., 2016; Dittberner et al., 2018). Analysis of herbarium and fossilized plant remains suggest that *SS* and *SD* have changed in response to atmospheric CO2 concentration over evolutionary time, probably to enable adjustments to *gsmax* and CO2 diffusion into the leaf (Woodward, 1987; Dilcher et al., 2000; Franks and Beerling, 2009). In samples from periods when CO2 concentrations were low, a reduction in *SS* and an increase in *SD* have been observed. On the other hand, when atmospheric CO2 levels have been high, *SS* has increased and *SD* decreased. Such adaptive responses to CO2 are also found in many extant lineages; however, this is not always the case in all species surveyed (Casson and Gray, 2008; Haworth et al., 2013; Field et al., 2015).

Although various combinations of *SS* and *SD* can result in similar alteration to *gsmax*, there are limitations as to how much of the epidermis can be patterned by stomata. First, other functionally important leaf structures such as veins and trichomes are also absolutely required. Second, stomata need to be spaced by at least one epidermal cell to function efficiently (Franks and Farquhar, 2007; Dow et al., 2014b). Therefore, changes to *SS* and *SD* are limited to a finite portion of the epidermis (Franks et al., 2009; Franks and Beerling, 2009; de Boer et al., 2016). In general, plants optimize *gsmax* through investing in increases in *SD* coupled with reductions in *SS* (Franks and Beerling, 2009; de Boer et al., 2012). According to Franks and Beerling (2009) and Franks and Farquhar (2007), changes toward increased *SD* in combination with reduced *SS* could maintain or improve total pore area (due to increased *SD*) but can also provide a shorter diffusion path (due to the smaller pore depth), potentially resulting in improved gas exchange.

While small *SS* coupled with high *SD* often leads to a higher *gsmax*, it is also possible for *gsmax* to be reduced by a smaller *SS* alone. Decreases in *gsmax* due to a smaller *SS* have been associated with higher water conservation, as reported for plants exposed to drought (Doheny-Adams et al., 2012) and ABA treatment (Franks and Farquhar, 2001). Smaller stomata are also associated with improved WUE in *Arabidopsis thaliana* (Dittberner et al., 2018); and rice varieties with smaller *SS* have the ability to strongly decrease *gs* under drought (Ouyang et al., 2017). Growth under low soil moisture conditions has been shown to cause a decrease in *SS* in several species (Xu and Zhou, 2008; Doheny-Adams et al., 2012; Sun et al., 2014; Zhao et al., 2015), but the effect on *SD* is less consistent (Clifford et al., 1995; Xu and Zhou, 2008; Doheny-Adams et al., 2012; Sun et al., 2014; Zhao et al., 2015). Stomatal size and density responses to vapor pressure deficit (VPD) are also variable. Under high VPD conditions, the woody angiosperm, *Toona ciliata*, displays smaller *SS* and higher *SD* (Carins Murphy et al., 2014), while tomato and sweet pepper show decreases in both stomatal traits (Bakker, 1991), and in poplar, changes in *SD* are dependent on CO2 concentration. (Miyazawa et al., 2006). Thus, changes in *SS* and *SD* in response to soil moisture or VPD appear to be specific to species and environmental variables (Bakker, 1991; Miyazawa et al., 2006; Xu and Zhou, 2008; Sun et al., 2014). Nutrient availability can also affect plant development. However, as described for soil moisture and VPD responses, adjustments in stomatal development in response to nutrient availability appear to be variable with no consistent response emerging (Gao et al., 2006; Sekiya and Yano, 2008; Yan et al., 2012; Sun et al., 2014; Hepworth et al., 2016).

## ARE SMALL STOMATA FASTER?

Small stomatal size can provide a reduction in total leaf pore area and might also facilitate faster aperture response (Franks and Beerling, 2009; Drake et al., 2013; Lawson and Blatt, 2014). The higher cell surface area to volume ratio of smaller cells is believed to permit faster ion fluxes, leading to faster guard cell turgor changes and a more rapid *gs* response (Lawson and Vialet-Chabrand, 2019). This faster stomatal behavior in plants with smaller *SS* has been observed in response to changes in light intensity across species of *Banksia*, rainforest trees, and in cereal species with dumbbell-shaped guard cells (Drake et al., 2013; McAusland et al., 2016; Kardiman and Raebild, 2017). However, although rapid stomatal movements might help to maximize WUE under fluctuating light environments, this is unlikely to have much impact on water loss over long periods of water stress under field conditions.

*SS* is clearly not the only anatomical trait influencing stomatal behavior. The shape of guard cells and the presence of subsidiary cells are also suggested to impact on stomatal responses (as discussed in "Stomatal morphology and improved WUE" below). In addition, the distribution of stomata between leaf abaxial and adaxial surfaces may also affect plant responses to environmental stresses. For example, stomata on the abaxial surfaces of wheat leaves show a stronger decrease in *gs* than adaxial stomata when they are exposed to water stress (Lu, 1989), and abaxial and adaxial stomata of cotton show differing responses to light quality (Lu et al., 1993). Moreover, as shown by Elliott-Kingston et al. (2016), Haworth et al. (2018), and McAusland et al. (2016), simple differences in *SS* do not always correlate with stomatal speed, especially when comparing distant taxa. Comparisons of cultivars or mutants of the same species with altered *SS*, but similar *SD*, would improve our understanding of the effect of guard cell size on speed of stomatal movement and explore if there is potential for *SS* as trait for improving WUE. Although a correlation between *SS* and genome size has been documented (Beaulieu et al., 2008; Jordan et al., 2015; Monda et al., 2016), the genetic and molecular mechanisms regulating *SS* remain unstudied, which currently limits our understanding of this trait.

### TARGETED CHANGES IN *SD* LEADING TO ALTERATIONS IN WUE