# Linking stomatal size and density to water use efficiency and leaf carbon isotope ratio in juvenile and mature trees

Peter Petrík<fnref n="1" />,<fnref n="2" /> ID | Anja Petek-Petrík<fnref n="1" /> ID | Laurent J. Lamarque<fnref n="3" />,<fnref n="4" /> ID |
Roman M. Link<fnref n="1" /> ID | Pierre-André Waite<fnref n="1" />,<fnref n="5" />,<fnref n="6" /> ID | Nadine K. Ruehr<fnref n="2" /> ID |
Bernhard Schuldt<fnref n="1" /> ID | Vincent Maire<fnref n="3" /> ID

**Correspondence**

Peter Petrik,

Email: peter.petrik@tu-dresden.de

**Funding information**

Waldklimafonds, Grant/Award Number:

NONNATIVE; Helmholtz Initiative and

Networking fund, Grant/Award Number:

W2/W3-156

Edited by J. Flexas

**Abstract**

Water-use efficiency (WUE) is affected by multiple leaf traits, including stomatal morphology. However, the impact of stomatal morphology on WUE across different ontogenetic stages of tree species is not well-documented. Here, we investigated the relationship between stomatal morphology, intrinsic water-use efficiency (iWUE) and leaf carbon isotope ratio (δ¹³C). We sampled 190 individuals, including juvenile and mature trees belonging to 18 temperate broadleaved tree species and 9 genera. We measured guard cell length (GCL), stomatal density (SD), specific leaf area (SLA), iWUE and bulk leaf δ¹³C as a proxy for long-term WUE. Leaf δ¹³C correlated positively with iWUE across species in both juvenile and mature trees, while GCL showed a negative and SD a positive effect on iWUE and leaf δ¹³C. Within species, however, only GCL was significantly associated with iWUE and leaf δ¹³C. SLA had a minor negative influence on iWUE and leaf δ¹³C, but this effect was inconsistent between juvenile and mature trees. We conclude that GCL and SD can be considered functional morphological traits related to the iWUE and leaf δ¹³C of trees, highlighting their potential for rapid phenotyping approaches in ecological studies.

## 1 | INTRODUCTION

Water-use efficiency (WUE) reflects the balance between carbon gain and water loss in plants (Leakey et al. 2019; Brendel et al. 2021; Vadez et al. 2023). Intrinsic water-use efficiency (iWUE) indicates a momentary balance of leaf carbon and water fluxes and corresponds

to the ratio of net CO₂ assimilation rate (A_n) to stomatal conductance to water vapour (g_s) (Roussel et al. 2009; Petek-Petrik et al. 2023). Higher iWUE can increase the establishment and survival of plants under water-deficit conditions (Ehleringer and Driscoll 2022). Enhancing iWUE is crucial for maximizing forest carbon assimilation capacity while conserving water resources (Zhang et al. 2023; Petrik et al. 2024).

This is an open access article under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

© 2024 The Author(s). Physiologia Plantarum published by John Wiley & Sons Ltd on behalf of Scandinavian Plant Physiology Society.

<footnote n="1">¹Chair of Forest Botany, Institute of Forest Botany and Forest Zoology, Technical University of Dresden (TUD), Tharandt, Germany</footnote>

<footnote n="2">²Institute of Meteorology and Climate Research - Atmospheric Environmental Research (IMK-IFU), KIT-Campus Alpin, Karlsruhe Institute of Technology (KIT), Garmisch-Partenkirchen, Germany</footnote>

<footnote n="3">³Département des Sciences de l'environnement, Université du Québec à Trois-Rivières, Trois-Rivières, QC, Canada</footnote>

<footnote n="4">⁴Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, Québec, QC, Canada</footnote>

<footnote n="5">⁵French Agricultural Research Centre for International Development (CIRAD), UPR AIDA, Montpellier, France</footnote>

<footnote n="6">⁶Agroecology and Sustainable Intensification of Annual Crops (AIDA), CIRAD, Université de Montpellier, Montpellier, France</footnote>
For long-term WUE, leaf carbon isotope composition (δ¹³C) is often used as a proxy because of the preference for the lighter isotope during physical and chemical processes involved in CO₂ uptake and assimilation (Farquhar et al. 1989; Ma et al. 2023). The preference for the lighter ¹²C isotope during CO₂ uptake and assimilation results in discrimination of the heavier ¹³C isotope. This discrimination is more pronounced when leaf internal CO₂ concentrations are higher, for instance when stomata are fully open due to more intense gas exchange via stomata, which in turn is associated with a lower iWUE (Impa et al. 2005). Thus, iWUE and δ¹³C are critical traits affecting tree water-use use for carbon assimilation, growth and survival across different time scales under water-deficit conditions, and they are of vital importance in the context of increasing evaporative demand due to climate change (Ehleringer and Driscoll 2022; Zhang et al. 2023; Puchi et al. 2024).

Both iWUE and δ¹³C of plants are affected by multiple physiological and morphological traits such as stomatal morphology, cuticular conductance, mesophyll conductance, leaf nitrogen, respiration rates (Buckley and Warren 2014; Bucher et al. 2016; Cardoso et al. 2020; Paillassa et al. 2020; Eckardt et al. 2023; Petrík et al. 2023; Kurjak et al. 2024). Ontogeny can also play a crucial role in shaping the leaf physiology, anatomy and morphology of trees across different life stages. Studies have shown that as trees develop, there are significant changes in their leaf morpho-physiological traits such as photosynthetic pigment concentration, dark respiration, δ¹³C (Fortunel et al. 2019) and photosynthetic efficiency (Ishida et al. 2005). Understanding particularly the phenotypic and ontogenetic constraints of iWUE would allow for better insights into the impacts of rising evaporative demand and more frequent drought periods (Grossiord et al. 2020; Vicente-Serrano et al. 2020; De Souza et al. 2023).

We chose here to specifically analyse the influence of stomatal morphological traits on iWUE and leaf δ¹³C as the characterization of these traits may represent an affordable and robust method for a rapid and mass phenotyping of tree water-use in field and experimental studies. So far, most studies focused on linking stomatal morphology to iWUE in crops (Andrade et al. 2022; Huang et al. 2022; Ozeki et al. 2022) or used model plant species like *Arabidopsis* and poplars (Guo et al. 2019; Jiao et al. 2022). There are some studies that focused on tree species, but these studies only captured intra-specific variability and did not include the effect of ontogeny (Cregg et al. 2000; Dillen et al. 2008; Roussel et al. 2009; Cao et al. 2012). Liu et al. (2018) found quadratic relationships between GCL, SD and WUE among tree species in global meta-analysis, but the WUE was derived from empirical relationships based on temperature and precipitation data rather than direct measurements. A comprehensive experimental analysis of inter-specific variability and coordination between the stomatal morphology and iWUE in forest tree species is lacking thus far. It, therefore, remains inconclusive whether stomatal morphological traits such as guard cell length (GCL) and stomatal density (SD) affect the water-use efficiency in tree species across ontogenetic stages, and whether they can be considered as robust functional traits associated with the drought tolerance in trees.

Photosynthetic activity of plants can adjust to changes in irradiance in seconds, but the time lag in stomatal responses limits the CO₂

uptake and therefore constrains photosynthesis and limits iWUE (Lawson et al. 2012; Nguyen et al. 2023). Several studies have reported that smaller stomata respond faster to changes in environmental conditions than larger stomata (Lawson et al. 2014; Kardiman and Raebild 2018; Durand et al. 2019), which can lead to higher long-term WUE (Drake et al. 2013; McAusland et al. 2016; Haworth et al. 2021). Stomatal size is also positively correlated with operational g_s; therefore, plants with smaller stomata can limit their maximal transpiration, potentially positively affecting iWUE (Fanourakis et al. 2015). Multiple gene-manipulation studies have shown that a reduction of stomatal size leads to enhanced iWUE in plants (Lawson et al. 2014; Mohammed et al. 2019; Jiao et al. 2023). This is particularly true in crops, and as a result, stomatal morphology is already used in crop breeding programmes that aim to create varieties with greater resistance to drought (Robertson et al. 2021; Xiong et al. 2022). If the negative relationship between stomatal size (guard cell length, GCL) and iWUE also holds true in trees across ontogenetical stages, this could further support phenotyping efforts for the evaluation of the water-use ability of tree populations.

SD is also a common functional trait related to plants WUE. Multiple studies have found a significant impact of SD on the WUE of plants under well-watered but also drought stress conditions. Several gene-manipulation studies have found negative relationships between SD and iWUE or δ¹³C in *Arabidopsis* (Franks et al. 2015), various crop species (Liu et al. 2015; Guo et al. 2019; Li et al. 2020; Pitaloka et al. 2022), in poplars (Liu et al. 2021; Jiao et al. 2022) and among tropical trees (Pan et al. 2024). Nevertheless, there is some evidence that higher SD can also be associated with a greater iWUE in plants (Xu et al. 2008; Naz et al. 2010; Zhao et al. 2015; Stojnić et al. 2019; Bhaskara et al. 2022; Al-Salman et al. 2023; Caine et al. 2023), or correlate positively with assimilation without offsetting iWUE (Tanaka et al. 2013). SD is usually negatively correlated with GCL as there is a trade-off between stomatal size and frequency (Franks and Beerling 2009; Doheny-Adams et al. 2012; Driesen et al. 2023). The increase of SD and reduction of stomatal size is a common acclimation response to drought stress in trees (Dunlap and Stetter 2001; Pearce et al. 2006; Boughalleb et al. 2014; Stojnić et al. 2015). Typically, SD and GCL show a negative correlation across genera due to spatial constraints on the leaf (Liu et al. 2023). In contrast, gene manipulation in crops can reduce SD disproportionally (–80%) compared to the increase of GCL (+20%), which might not be realistic for natural populations (Franks et al. 2015). The relationship between SD and iWUE of trees is therefore probably connected to changes in stomatal size.

The leaf morphology can also constrain the iWUE via changes in CO₂ and H₂O pathways throughout leaf tissues (Carriquí et al. 2015; Trueba et al. 2022). Leaf morphology can be apprehended by the specific leaf area (SLA), i.e., the inverse of leaf mass per area, a widely used functional trait in plant ecology (Tian et al. 2016). SLA decreases in plants with thicker leaves (Vile et al. 2005; Homeier et al. 2021). Multiple studies have found that SLA is negatively related to iWUE and δ¹³C in crops (Reddy et al. 2020a; Reddy et al. 2020b), shrubs (Horike et al. 2021) and tree species (Ge et al. 2022). The correlation between SLA and iWUE might be caused by anatomical differences
that affect the mesophyll tissue surface area and mesophyll conductance (Baird et al. 2017). SLA can also influence photosynthetic capacity (Liu et al. 2010) and quantum yield (Petek-Petrik et al. 2024), which may be constraining factors for iWUE. This raises the question of whether the reported association between SLA and iWUE is a general pattern, which would allow using SLA, a widely available functional trait, as a proxy of the iWUE of plants in ecological studies.

In this study, we took advantage of two experiments on temperate mature and juvenile trees (18 tree species in total) to quantify how stomatal and leaf morphology affect the short-term iWUE and long-term δ¹³C estimates of tree water-use. We hypothesized that i) higher values of GCL are associated with a lower iWUE and δ¹³C, ii) the degree of stomatal density affects iWUE and δ¹³C, iii) SLA is negatively related to iWUE and δ¹³C, iv) the relationships between morphological (GCL, SD, SLA) and physiological (iWUE, δ¹³C) traits do not differ between juvenile and mature tree species.

# 2 | MATERIALS AND METHODS

## 2.1 | Juvenile trees experimental set-up

The juvenile tree measurements were conducted in the Botanical Garden of the University of Würzburg, Germany (49°45′53.542″N, 9°55′52.92″E) in June 2022. The site has a temperate climate with an average temperature of 11.7°C and an annual precipitation of 561 mm in 2022 (Deutscher Wetterdienst, 2022). Ten individuals each from ten broadleaved tree species were used for the measurements: *Acer pseudoplatanus* (ACPS), *Aesculus hippocastanum* (AEHI), *Betula maximowicziana* (BEMA), *Betula pendula* (BEPE), *Fagus sylvatica* (FASY), *Quercus petraea* (QUPE), *Quercus rubra* (QURU), *Sorbus aucuparia* (SOAC), *Tilia cordata* (TICO) and *Tilia tomentosa* (TITO). The trees of all species except ACPS and SOAC had heights ranging from 50 cm to 120 cm and were between 3–5 years old. The height of ACPS and SOAC individuals ranged from 150 cm to 180 cm, ACPS individuals were 8 years old and SOAC individuals were 6 years old. The juvenile trees were planted in an inorganic sand/loam mixture in 10 L pots and 20 L pots (ACPS, SORB) during the spring of 2022. The trees were regularly irrigated to maintain optimal water status. The leaves for all measurements were sampled from the upper part of the crown and represented sun leaves.

## 2.2 | Mature trees experimental set-up

The mature tree measurements were conducted on the Campus of the Université du Québec à Trois-Rivières, Canada (46°20′49.041″N, 72°34′40.932″W) in August/September 2022. The site is located on sandy soils representative of the retreat of the Champlain Sea, and in a temperate climate zone with average annual temperature and annual precipitation around 5.2°C and 872 mm (as rainfall), respectively (MDDELCC, 2015). Six individuals each from nine broadleaved tree species were tagged within the Campus area and used for the

measurements. The tree species included: *Acer platanoides* (ACPL), *Acer rubrum* (ACRU), *Acer saccharinum* (ACSA), *Betula populifolia* (BEPO), *Populus grandidentata* (POGR), *Populus tremuloides* (POTR), *Quercus pensylvanica* (PRPE), *Quercus rubra* (QURU) and *Tilia americana* (TIAM). All mature trees had heights ranging between 8–15 m with the exception of TIAM, which measured around 4 m. The vegetation season and measurement period of 2022 received evenly distributed precipitation and, therefore, the trees were not drought-stressed, which is also visible in our leaf water potential measurements (Table 1). The leaves for all measurements were sampled with telescopic scissors from the sun-exposed Southern side in the lower third of the crown.

## 2.3 | Gas-exchange measurements

Gas-exchange measurements were conducted between 1st and 9th of June 2022 of juvenile trees and between 25th of August and 8th of September 2022 on mature trees. The time periods for the measurements were 9:30–12:00 and 13:30–16:00 to avoid a mid-day depression. Gas-exchange measurements were done with a Li-6800 (LI-COR) equipped with a standard leaf chamber with 3 cm² for juvenile trees and with 6 cm² cuvette for mature trees. The chamber conditions were set to 1000 µmol m⁻² s⁻¹ PAR intensity, 420 ppm reference CO₂ and fan speed of 10000 rpm in both experiments. The air temperature in the cuvette was 22 ± 0.95 °C (mean ± SE) for mature trees and 26 ± 1.05°C for juvenile trees, the relative humidity in the cuvette was averaging at 60 ± 1.6% for mature trees and 60 ± 3% for juvenile trees. Leaf gas-exchange on mature trees was measured at sun-exposed leaves from the lower third of the tree crown, immediately after excision. Leaf gas-exchange of juvenile trees was typically measured at intact, sun-exposed leaves from the upper third of their crown. For juvenile ACPS and SORB, we used excised branches originating from the upper third of the tree crown, which were immediately measured. In total, we measured gas exchange on 154 trees belonging to 18 tree species (mature: *n* = 54; juvenile: *n* = 100). Leaf gas-exchange was measured 4–5 times per individual in mature trees and 3–4 times in juvenile trees during the experimental period. The measurements were averaged per individual for further analyses. The intrinsic water-use efficiency (iWUE) was calculated as a ratio between assimilation rate (A) and stomatal conductance (g_s); iWUE = A/g_s.

## 2.4 | Water potential measurements

The leaf water potential (WP) of both juvenile and mature trees was measured periodically to make sure that the trees were not drought-stressed. All juvenile trees were watered regularly (1–2× per week) and their leaf WP was measured each morning before gas-exchange measurements to test their water status (Table 1). The leaf WP of juvenile trees was measured with a Scholander pressure chamber (Model 1505D, PMS Instruments) on petioles of leaves excised from the upper part of the tree crowns, within 3 minutes after the excision.
The leaves of mature trees adjacent to the leaves used for the gas-exchange measurements were stored in plastic bags with a wet tissue and placed in a mobile cooler. In the afternoon of the same day (ca. 4–5 pm), their leaf WP was measured with a Scholander pressure chamber (Model 1505D, PMS Instruments) on petioles of the excised leaves (Table 1).

The water potential measurements confirmed that none of the species were drought-stressed during the measurement periods neither in juvenile nor mature trees.

## 2.5 | Stomatal morphology

The stomatal imprints were done with the 'collodion method', where transparent nail polish is applied to the abaxial side of the leaves, as all sampled species have minimal stomatal occurrence on upper side of their leaves. After 2–3 minutes, the nail polish layer was transferred to a microscope slide using transparent tape (Petrík et al. 2022). The stomatal imprints from mature trees were collected after each gas-exchange measurement, while for juvenile trees they were taken only after the first round of measurements. The imprints were collected from the same area where leaf gas-exchange was measured. Therefore, the spatial variability of the stomatal morphology within the leaf should match the spatial variability of gas-exchange. The stomatal imprints were taken for 10 individuals per species, 4–5 imprints per individual for mature trees and one imprint per individual for juvenile trees. From these imprints, the digital photographs using Levenhuk MED 30 T equipped with Delta Optical DLT-Cam Pro 12MPx were taken at 40×10 resolution. The guard cell length (GCL) and stomatal density (SD) were measured from these digital photos with ImageJ software (Schneider et al. 2012). The GCL was measured for 3 random stomata per photo and these values were averaged per individual (three stomata per individual for juvenile and 12–15 stomata per individual for mature trees). The number of stomata for the entire area of the photo (0.416 mm²) was measured and was further recalculated to SD per 1 mm² (one SD value per individual for juvenile and three SD values averaged per individual for mature trees).

## 2.6 | Specific leaf area

The leaves used for the first round of gas-exchange measurements for mature trees were taken for specific leaf area (SLA) estimation, while SLA was deduced from additional leaves sampled at the end of the experiment for juvenile trees. Three leaves from the upper third of the crown were sampled from each mature tree individual. The mature tree leaves were scanned with a Perfection V800 scanner (Epson) and juvenile tree leaves with an A3 scanner (Perfection 12000XL, Seiko Epson) and their leaf area was measured with ImageJ software. Afterwards, the leaves were oven-dried at 70 °C for 48 h. Subsequently, SLA of each leaf was calculated as $SLA = \frac{\text{leaf area}}{\text{dry mass}}$. The values were averaged for each individual.

## 2.7 | Carbon isotope analysis

The same leaf samples used for SLA measurement were further ground to fine powder and stored in a freezer for the carbon isotope ($\delta^{13}\text{C}$) analysis. Leaf $\delta^{13}\text{C}$ isotopic ratios of the mature tree's samples were determined using an elemental analyser coupled with an isotope ratio mass spectrometer (EA-IRMS, Agilent technology). The juvenile tree samples were analysed at the Centre for Stable Isotope Research and Analysis (KOSI), University of Göttingen. The leaf $\delta^{13}\text{C}$ of juvenile trees was measured with a Delta Plus Isotope mass ratio spectrometer (Finnigan MAT), a Conflo III interface (Thermo Electron Corporation) and a NA2500 elemental analyser (CE-Instruments). The replicate analyses of isotopic standard reference materials USGS 40 ($\delta^{13}\text{C} = -26.39\text{‰}$) and USGS 41 ($\delta^{13}\text{C} = 37.63\text{‰}$) were used to normalize the isotopic values of working standards to the Vienna Pee Dee Belemnite ($\delta^{13}\text{C}$) scales. Isotope values are expressed in $\delta$ notation following the formula $\delta X (‰) = [(R_{\text{sample}}/R_{\text{standard}}) - 1] \times 103$, where X represents $^{13}\text{C}$ and R is $^{13}\text{C}/^{12}\text{C}$ isotopic ratio. Working standards were analysed after every ten samples to monitor instrument performance and ensure data normalization. The precision of the laboratory standards was $\pm 0.3\text{‰}$ for C and N.

## 2.8 | Statistical analysis

All statistical analyses were conducted in R 4.2.1 software (R Core Team), using trait data at the individual (tree) level ($n = 10$ individuals $\times 10$ species for the juvenile tree stage, and $n = 6$ individuals $\times 9$ species for the mature tree stage). Prior to analyses, the normal distribution of all traits within species was tested with the Shapiro-Wilk test and the homoscedasticity between species was tested with the Bartlett's test. Variation in stomatal and leaf morphology among species was conducted using simple ANOVAs with species as fixed factor and Tukey's HSD post-hoc tests to test variation in the measured traits among species (Table 1).

The influence of stomatal and leaf morphology on water-use efficiency and carbon isotope ratio variation was studied using linear models at species level (across species) and linear mixed models at individual level (within species). Linear regression was used to test the impact of morphological traits on iWUE and $\delta^{13}\text{C}$, and to test the relationship between iWUE and $\delta^{13}\text{C}$ on species level for the juvenile and mature trees separately (Figures 1-3). The individual-level relationship between morphological traits, iWUE and $\delta^{13}\text{C}$ was analysed with linear mixed-effects models fitted with R package lme4 v1.1–35.1 (Bates et al. 2015). Models were fitted using stomatal density, guard cell length and specific leaf area as predictors, with separate sets of parameters for each ontogenetic class. To account for the heterogeneity among species and ontogenetic stages, we added a random intercept for species separated into juvenile and mature state. All three predictor variables were natural log-transformed prior to analysis to account for their strict lower bound at zero and to reduce the leverage of few observations with high values for one or more of the predictors. After log-transformation, the predictors were scaled and centred to facilitate comparison between parameter estimates and to improve the interpretability of the intercept. We used custom contrasts specified via R's formula interface to estimate a
separate intercept and parameter set for each ontogenetic stage, resulting in the following model:

$$y_i = \alpha_s + \beta_{1s} \cdot SD_i + \beta_{2s} \cdot GCL_i + \beta_{3s} \cdot SLA_i + \alpha_{js} + \epsilon_i$$
$$\alpha_{js} \sim \text{Normal}(0, \tau_{sp})$$
$$\epsilon_i \sim \text{Normal}(0, \sigma),$$

where $y_i$ is the observed value of the response (iWUE or δ¹³C) for observation; $i$, $\alpha_s$, $\beta_{1s}$, $\beta_{2s}$ and $\beta_{3s}$ are the estimated intercept and slopes for the values of SD, GCL and SLA, respectively for ontogenetic stage s (adult or juvenile); $\alpha_{js}$ is a random effect for species j; stage s and $\epsilon_i$ are the model residuals. The random model components $\alpha_{js}$ and $\epsilon_i$ were assumed to be normally distributed around zero with standard deviation $\tau_{sp}$ and $\sigma$, respectively.

Models were fitted with restricted maximum likelihood. Inference was based on Wald t-tests with Satterthwaite's approximation to the degrees of freedom based on R package lmerTest v3.1-3 (Kuznetsova et al., 2017). Model assumptions were tested by inspection of residual diagnostic plots. As there were indications of increasing variance with the mean and a non-normality of the residuals, the model for WUE was refitted after log-transformation of the response. Estimates of the explained variance of the marginal and conditional predictions were computed according to Nakagawa et al. (2017) using R package MuMln v1.47.5 (Barton, 2023). Parametric confidence bounds on partial predictions were computed with R package ciTools v0.6.1 (Haman & Avery, 2017).

*Supplementary analyses* Pearson correlations between traits were assessed and visualized with R package corrmorant (Link 2020).

# 3 | RESULTS

## 3.1 | Species level relationships between leaf and stomatal morphology, water-use efficiency and leaf carbon isotope ratio

Across species, GCL was a significant predictor of iWUE and leaf δ¹³C. The increase of GCL corresponded to a reduction of iWUE (Figure 1A,B) and leaf δ¹³C (Figure 2A,B) in both juvenile and mature trees. All significant correlations for iWUE exhibited an R² > 0.5, while those for δ¹³C demonstrated R² > 0.4. The GCL and SD were negatively correlated for both juvenile and mature tree species (Figure S1). Therefore, SD showed a positive trend with iWUE and δ¹³C, but this trend was significant only for mature trees (Figures 1C and 2C). SLA showed a negative impact on both iWUE and leaf δ¹³C, but the relationship was significant only for the leaf δ¹³C of juvenile trees (Figure 2F).

The iWUE derived from gas-exchange measurements corresponds to leaf δ¹³C among tree species. The iWUE and leaf δ¹³C showed significant positive linear relationships for both juvenile and mature trees (Figure 3A,B). The relationship between iWUE and δ¹³C

showed greater explanatory power for mature (R² = 0.89) than for juvenile (R² = 0.59) trees.

## 3.2 | Individual level relationships between leaf and stomatal morphology, water-use efficiency and leaf carbon isotope ratio

The mixed effects model of iWUE as a function of GCL, SD and SLA at the individual level explained 63.1% of the variance in iWUE, of which 45.0% were explained by the fixed effects alone (Table 2). On average, iWUE was higher for juvenile than for mature trees. iWUE was moreover significantly lower for leaves with a higher average guard cell length both for mature and juvenile trees (Figure 5A). In addition, the iWUE of the leaves of mature trees was lower for leaves with higher SLA (Figures 4C and 5A). Notably, SD did not have a significant effect on iWUE after accounting for the effect of GCL and SD (Figures 4C and 5A).

An analogous model of leaf δ¹³C at the individual level explained 82.8% of the variance in leaf δ¹³C, of which 56.8% were explained by GCL, SD and SLA. Here, only the GCL for juvenile trees had a significant impact, while the other variables did not (Figures 4D and 5B). The partial effects of the model showed similar patterns as for iWUE, where increasing GCL had a negative impact on leaf δ¹³C.

## 3.3 | Variation in stomatal and leaf morphology among species and ontogenetic stages

All tested morpho-physiological traits differed significantly among species for both juvenile and mature stages (Table S1). The averages with 95% confidence intervals and results of Tukey's HSD post-hoc analysis for each measured trait are presented in Table 1. The lowest iWUE was observed for *Betula* sp. at both juvenile and mature stages (35–65 µmol mmol⁻¹ average range) and for mature *Prunus pensylvanica* (35 µmol mmol⁻¹). The highest iWUE was observed among the mature trees of *Acer* sp. and *Quercus rubra* (averages between 80 and 90 µmol mmol⁻¹) and among juvenile *Quercus petraea* and two *Tilia* sp. (averages between 95 and 114 µmol mmol⁻¹). The aforementioned species had an approximately 2.5× higher iWUE than species with a low iWUE in both juvenile and mature stages. The data from both experiments showed a dependency between GCL and SD at the species level (Figure S1). Accordingly, species with high GCL, like *Betula* sp., had a lower SD and species with low GCL, like *Acer* sp. and *Quercus* sp., had a higher SD in our study (Table 1). The differences in specific leaf area (SLA) between species were greater among the juvenile trees than between mature trees (Table 1). The *Betula* sp. had the greatest SLA among juvenile trees and *Aesculus hippocastanum* the lowest. The overall mean SLA of mature trees was lower than that of juvenile trees. The variability of SLA between species was much higher among juvenile trees than among mature trees (Table 1).
<table><caption>TABLE 1 Species-level averages of leaf water potential (WP), specific leaf area (SLA), guard cell length (GCL), stomatal density (SD), assimilation rate (A), stomatal conductance (gs), intrinsic water-use efficiency (iWUE) and carbon isotope discrimination (δ¹³C) with 95% confidence intervals and lower-case letter representing results from Tukey's HSD post-hocs. N = 10 and 9 tree species for the juvenile and mature tree stage, respectively.</caption><thead><tr><th>Species</th><th>ID</th><th>WP (MPa)</th><th>SLA (cm² g⁻¹)</th><th>GCL (µm)</th><th>SD (N mm⁻¹)</th><th>A (µmol m⁻² s⁻¹)</th><th>g<sub>s</sub> (mmol m⁻² s⁻¹)</th><th>iWUE (µmol mmol⁻¹)</th><th>δ¹³C (%)</th></tr></thead><tbody><tr><td colspan="10"><strong>Juvenile trees</strong></td></tr><tr><td>Acer pseudoplatanus</td><td>ACPS</td><td>-0.66 ± 0.09</td><td>145.45 ± 19.7 cd</td><td>18.4 ± 1.1cde</td><td>233.7 ± 32.6d</td><td>12.01 ± 2a</td><td>207.00 ± 39.0a</td><td>62.03 ± 5.3 cd</td><td>-27.32 ± 0.7de</td></tr><tr><td>Aesculus hippocastanum</td><td>AEHI</td><td>-0.78 ± 0.16</td><td>116.28 ± 13.6d</td><td>17.19 ± 1.1ef</td><td>274.7 ± 51.5 cd</td><td>9.41 ± 1.1ab</td><td>120.0 ± 19.2b</td><td>80.1 ± 8bc</td><td>-26.58 ± 0.2 cd</td></tr><tr><td>Betula maximowicziana</td><td>BEMA</td><td>-0.71 ± 0.09</td><td>242.17 ± 32.1ab</td><td>33.09 ± 3.5a</td><td>272.3 ± 46.7 cd</td><td>8.69 ± 1.2b</td><td>193.6 ± 51.2a</td><td>47.12 ± 7.4d</td><td>-29.47 ± 1f</td></tr><tr><td>Betula pendula</td><td>BEPE</td><td>-0.47 ± 0.10</td><td>273.17 ± 29.5a</td><td>31.15 ± 2.5a</td><td>250.6 ± 57.6d</td><td>13.34 ± 2.3a</td><td>209.8 ± 46.0a</td><td>65.02 ± 5bcd</td><td>-29.50 ± 0.4f</td></tr><tr><td>Fagus sylvatica</td><td>FASY</td><td>-0.72 ± 0.09</td><td>207.33 ± 11.5b</td><td>20.82 ± 1.6bcd</td><td>363.9 ± 72bc</td><td>8.08 ± 1.6b</td><td>109.9 ± 11.8bc</td><td>70.25 ± 14.9bcd</td><td>-27.03 ± 0.5de</td></tr><tr><td>Quercus petraea</td><td>QUPE</td><td>-0.68 ± 0.09</td><td>160.65 ± 12.9c</td><td>14.84 ± 1.1b</td><td>650.6 ± 58.2a</td><td>10.48 ± 1.8ab</td><td>97.6 ± 29.0bc</td><td>114 ± 12.9a</td><td>-24.60 ± 0.3a</td></tr><tr><td>Quercus rubra</td><td>QURU</td><td>-0.69 ± 0.05</td><td>148.74 ± 10.2 cd</td><td>22.74 ± 0.7f</td><td>662.7 ± 41.4a</td><td>7.98 ± 1.2b</td><td>136.9 ± 39.8bc</td><td>59.54 ± 18.4 cd</td><td>-26.36 ± 0.6bcd</td></tr><tr><td>Sorbus aucuparia</td><td>SOAU</td><td>-0.63 ± 0.09</td><td>171.48 ± 15.0c</td><td>21.76 ± 1.4bc</td><td>132.5 ± 23.3e</td><td>7.4 ± 1.1b</td><td>85.6 ± 15.3c</td><td>88.04 ± 7.7bc</td><td>-27.87 ± 0.4e</td></tr><tr><td>Tilia cordata</td><td>TICO</td><td>-0.57 ± 0.06</td><td>184.42 ± 16.9bc</td><td>16.55 ± 1.5ef</td><td>255.4 ± 57d</td><td>8.76 ± 1b</td><td>98.1 ± 11.7bc</td><td>95.68 ± 18.3a</td><td>-25.32 ± 0.5ab</td></tr><tr><td>Tilia tomentosa</td><td>TITO</td><td>-0.68 ± 0.10</td><td>210.92 ± 10.6b</td><td>17.8 ± 0.8def</td><td>462.7 ± 37.1b</td><td>10.88 ± 0.8a</td><td>124.4 ± 18.4b</td><td>89.82 ± 10.7ab</td><td>-25.80 ± 0.4bc</td></tr><tr><td colspan="10"><strong>Mature trees</strong></td></tr><tr><td>Acer platanoides</td><td>ACPL</td><td>-0.66 ± 0.14</td><td>129.22 ± 19.62b</td><td>17.9 ± 1.31c</td><td>524.9 ± 84.8ab</td><td>9.64 ± 1.37a</td><td>126.2 ± 21.1a</td><td>79.82 ± 8.42c</td><td>-29.18 ± 0.3b</td></tr><tr><td>Acer rubrum</td><td>ACSA</td><td>-0.90 ± 0.07</td><td>126.74 ± 9.32a</td><td>11.17 ± 1.25d</td><td>699.8 ± 27.5ab</td><td>10.13 ± 1.3ab</td><td>125.7 ± 25.7a</td><td>90.09 ± 25.14c</td><td>-27.64 ± 0.46a</td></tr><tr><td>Acer saccharinum</td><td>ACSX</td><td>-0.83 ± 0.16</td><td>143.67 ± 18.64a</td><td>11.19 ± 0.98d</td><td>695.8 ± 53.4b</td><td>13.54 ± 1.48b</td><td>181.2 ± 38.5b</td><td>84.18 ± 7.09c</td><td>-28.22 ± 0.4a</td></tr><tr><td>Betula populifolia</td><td>BEPO</td><td>-1.00 ± 0.11</td><td>134.66 ± 9.51e</td><td>36.72 ± 2.22a</td><td>183.4 ± 49.8b</td><td>13.53 ± 2.03b</td><td>393.1 ± 37.2d</td><td>35.04 ± 7.28a</td><td>-31.07 ± 1.03c</td></tr><tr><td>Populus grandidentata</td><td>POGR</td><td>-1.57 ± 0.16</td><td>141.43 ± 12.18b</td><td>17.24 ± 1.62c</td><td>429.7 ± 33.6b</td><td>13.77 ± 1.22b</td><td>276.0 ± 34.8c</td><td>53.41 ± 12.08b</td><td>-30.45 ± 0.75bc</td></tr><tr><td>Populus tremuloides</td><td>POTR</td><td>-1.65 ± 0.26</td><td>112.2 ± 16.23c</td><td>21.93 ± 1.98b</td><td>354.4 ± 54.4a</td><td>15.93 ± 1.24b</td><td>283.4 ± 35.3c</td><td>58.74 ± 6.79b</td><td>-29.58 ± 0.79b</td></tr><tr><td>Prunus pensylvanica</td><td>PRPE</td><td>-0.86 ± 0.17</td><td>149.58 ± 7.43d</td><td>26.9 ± 1.59b</td><td>338.7 ± 64.3b</td><td>8.91 ± 1.9a</td><td>254.7 ± 34.2bc</td><td>35.26 ± 6.65a</td><td>-30.78 ± 0.96bc</td></tr><tr><td>Quercus rubra</td><td>QURU</td><td>-1.07 ± 0.26</td><td>101.19 ± 4.88c</td><td>22.74 ± 0.91c</td><td>519.1 ± 55.5a</td><td>15.43 ± 2.44b</td><td>236.7 ± 57.0bc</td><td>80.18 ± 28.88c</td><td>-28.01 ± 0.86ab</td></tr><tr><td>Tilia americana</td><td>TIAM</td><td>-0.87 ± 0.11</td><td>112.02 ± 5.37 cd</td><td>23.97 ± 0.93bc</td><td>379.5 ± 45.2a</td><td>14.72 ± 0.68b</td><td>305.6 ± 31.6c</td><td>50.52 ± 6.86ab</td><td>-29.63 ± 0.71bc</td></tr></tbody></table>
**FIGURE 1** Species-level linear regressions between guard cell length (GCL), stomatal density (SD), specific leaf area (SLA) and intrinsic water-use efficiency (iWUE) for mature trees (A,C,E) and juvenile trees (B,D,F). The species-level averages are accompanied by 95% confidence intervals. Solid and dashed lines refer to significant and non-significant relationships on a 0.05% significance level, respectively. Regression analysis' sample size for mature trees is 9 and 10 for juvenile trees. Sample size for 95% confidence intervals per species is 10 individuals for juvenile and 6 individuals for mature trees.

<figure><img src="image_1.png" /></figure>

# 4 | DISCUSSION

## 4.1 | Guard cell length affects water-use efficiency and δ¹³C of trees

We observed significant negative relationships between GCL and both iWUE and δ¹³C for juvenile and mature trees both inter-specifically and intra-specifically (with the exception of mature δ¹³C within species). A higher guard cell length corresponded to a lower iWUE, as well as a longer-term WUE proxy of δ¹³C, thus confirming hypothesis 1. A negative relationship between stomatal size or GCL and iWUE has been previously reported mostly in crops and was explained by the faster response time of smaller stomata to changing

environmental conditions compared to larger stomata (Drake et al. 2013; Lawson and Blatt 2014; Kardiman and Raebild 2018; Dur-and et al. 2019). Lei et al. (2023) showed that larger stomata exhibited a decelerated response time to fluctuations in light intensity and dem-onstrated an overall diminished water-use efficiency (inferred from δ¹³C). Larger stomata can also have higher maximal gs, which increases transpiration and, therefore, can have a negative impact on iWUE (Fanourakis et al. 2015). A genetic manipulation experiment showed that rice mutants with reduced stomatal size exhibited increased iWUE compared to mutants with larger stomatal size (Pitaloka et al. 2022). Similarly, the iWUE in wheat cultivars was correlated negatively with stomatal size and transpiration rates (Li et al. 2017). Amitrano et al. (2021) found that lettuce exhibited a substantial 49% increase in iWUE
<figure><img src="image_2.png" /><figcaption>**FIGURE 2** Species-level linear regressions between guard cell length (GCL), stomatal density (SD), specific leaf area (SLA) and leaf carbon isotope ratio (δ¹³C) for mature trees (A,C,E) and juvenile trees (B,D,F). The species-level averages are accompanied by 95% confidence intervals. Solid and dashed lines refer to significant and non-significant relationships on a 0.05% significance level, respectively. Regression analysis' sample size for mature trees is 9 and 10 for juvenile trees. The sample size for 95% confidence intervals per species is 10 individuals for juvenile and 6 individuals for mature trees.</figcaption></figure>

that was associated with a reduction of stomatal size under different VPD treatments. Furthermore, exposure to drought stress led to the inhibition of stomatal development, resulting in smaller stomata and an increase of iWUE in cotton (Dubey et al. 2023). On the other hand, two studies focusing on the intra-specific variability of iWUE did not find a significant relationship between GCL and iWUE, most likely due to low GCL variability across poplar genotypes (Durand et al. 2019; Durand et al. 2020). The GCL is probably under strong intra-specific genetic control, as previously observed for different European beech provenances (Petrik et al. 2020). Our results showed that GCL had a significant impact on iWUE also within species and tends to impact the leaf δ¹³C of mature trees. The use of stomatal imprints is a cost-effective method to characterize trees' water-use efficiency variability compared with labour-intensive gas-exchange measurements or costly carbon isotope analysis. Our results support findings from crops that species with smaller stomatal cells with lower GCL have a higher

immediate leaf iWUE derived from gas-exchange and higher leaf δ¹³C as proxy for long-term WUE. The relationship is slightly weaker for intra-specific comparison at the individual level but is quite robust at the species level. The creation of stomatal imprints is significantly cheaper and faster than gas-exchange or δ¹³C measurements. Therefore, stomatal morphology traits can be measured more extensively in the field (more sites, higher sample size) compared to the other two methods, which highlights their potential value for large-scale phenotyping studies. The overall time efficiency is limited by the measurement of stomatal morphological parameters and stomatal density, which can be significantly improved by the implementation of machine learning or AI tools that automate the measurements (Casado-Garcia et al. 2020; Wu et al. 2024). Additionally, it is important to note that stomatal imprints primarily capture the water side of iWUE, and that photosynthetic efficiency must be characterised by other methods to fully understand iWUE constraints (Al-Salman et al. 2024).
<figure><img src="image_3.png" /><figcaption>**TABLE 2** Results of the mixed effects models testing the influence of stomatal (GCL, SD) and morphological (SLA) traits and genus on intrinsic water use efficiency (iWUE) and leaf carbon isotope ratio (δ¹³C). We used species (included separately for adult and juvenile stages of the same species) as a random effect, and fitted the models on a log scale with normal errors, corresponding to the following model equation: lmer(response ~ stage + stage: (sla + gcl + sd) + 0 + (1 | species:stage), data = data). Shown are the estimated values with their standard errors and 95% confidence intervals, the t-statistic and degrees of freedom based on Satterthwaite's approximation, and the corresponding p-values. Parameters significantly different from zero on a 95% level are highlighted in bold.</figcaption></figure>

<table><thead><tr><th>Parameter</th><th>Ontogeny</th><th>Estimate</th><th>Std.error</th><th>Lwr 95% CI</th><th>Upr 95% CI</th><th>t-statistic</th><th>df</th><th>p-value</th></tr></thead><tbody><tr><td colspan="9"><strong>Model for iWUE</strong></td></tr><tr><td rowspan="2">α<sub>s</sub> (Intercept)</td><td>Juvenile</td><td>4.286</td><td>0.054</td><td>4.168</td><td>4.403</td><td>78.818</td><td>12.784</td><td>&lt;0.001</td></tr><tr><td>Mature</td><td>3.881</td><td>0.085</td><td>3.706</td><td>4.056</td><td>45.246</td><td>31.215</td><td>&lt;0.001</td></tr><tr><td rowspan="2">β<sub>1</sub> (SD)</td><td>Juvenile</td><td>0.007</td><td>0.039</td><td>-0.071</td><td>0.085</td><td>0.188</td><td>52.876</td><td>0.851</td></tr><tr><td>Mature</td><td>0.124</td><td>0.090</td><td>-0.054</td><td>0.303</td><td>1.377</td><td>132.133</td><td>0.171</td></tr><tr><td rowspan="2">β<sub>2</sub> (GCL)</td><td>Juvenile</td><td>-0.212</td><td>0.053</td><td>-0.321</td><td>-0.104</td><td>-3.959</td><td>49.194</td><td>&lt;0.001</td></tr><tr><td>Mature</td><td>-0.144</td><td>0.067</td><td>-0.278</td><td>-0.009</td><td>-2.130</td><td>69.997</td><td>0.0376</td></tr><tr><td rowspan="2">β<sub>3</sub> (SLA)</td><td>Juvenile</td><td>0.053</td><td>0.037</td><td>-0.021</td><td>0.127</td><td>1.412</td><td>116.924</td><td>0.161</td></tr><tr><td>Mature</td><td>-0.176</td><td>0.085</td><td>-0.346</td><td>-0.006</td><td>-2.065</td><td>100.837</td><td>0.041</td></tr><tr><td>τ<sub>sp</sub></td><td></td><td>0.149</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>σ</td><td></td><td>0.213</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td colspan="9"><strong>Model for δ<sup>13</sup>C</strong></td></tr><tr><td rowspan="2">α<sub>s</sub> (Intercept)</td><td>Juvenile</td><td>-26.843</td><td>0.307</td><td>-27.566</td><td>-26.120</td><td>-87.310</td><td>7.194</td><td>&lt;0.001</td></tr><tr><td>Mature</td><td>-29.576</td><td>0.411</td><td>-30.451</td><td>-28.701</td><td>-71.804</td><td>15.656</td><td>&lt;0.001</td></tr><tr><td rowspan="2">β<sub>1</sub> (SD)</td><td>Juvenile</td><td>0.204</td><td>0.161</td><td>-0.115</td><td>0.524</td><td>1.264</td><td>105.781</td><td>0.208</td></tr><tr><td>Mature</td><td>-0.136</td><td>0.340</td><td>-0.808</td><td>0.536</td><td>-0.399</td><td>145.903</td><td>0.698</td></tr><tr><td rowspan="2">β<sub>2</sub> (GCL)</td><td>Juvenile</td><td>-0.785</td><td>0.226</td><td>-1.235</td><td>-0.335</td><td>-3.469</td><td>85.023</td><td>&lt;0.001</td></tr><tr><td>Mature</td><td>-0.396</td><td>0.287</td><td>-0.975</td><td>0.182</td><td>-1.380</td><td>44.570</td><td>0.174</td></tr><tr><td rowspan="2">β<sub>3</sub> (SLA)</td><td>Juvenile</td><td>-0.160</td><td>0.142</td><td>-0.441</td><td>0.121</td><td>-1.123</td><td>145.995</td><td>0.263</td></tr><tr><td>Mature</td><td>-0.261</td><td>0.332</td><td>-0.918</td><td>0.396</td><td>-0.785</td><td>139.41</td><td>0.434</td></tr><tr><td>τ<sub>sp</sub></td><td></td><td>0.920</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr><tr><td>σ</td><td></td><td>0.748</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td><td>NA</td></tr></tbody></table>

## 4.2 | Stomatal density and water-use efficiency

We observed that SD had a significant positive effect on iWUE and leaf δ¹³C of mature trees (p < 0.05) and a marginally significant impact on leaf δ¹³C (p = 0.08) of juvenile trees at the species level (hypothesis 2 confirmed). On the other hand, the mixed model showed no

impact of SD on individual-level iWUE or leaf δ¹³C. The discrepancies between the inter- and intra-specific comparison may in part result from the different aggregation levels (Pollet et al. 2015; Isasa et al. 2023). However, the disappearing SD effect when accounting for GCL is likely also driven by the relatively high correlation between the two variables. Leaf stomatal density can have a distinct effect on
<figure><img src="image_4.png" /><figcaption>**FIGURE 4** Partial effects of guard cell length, stomatal density, specific leaf area for the model of water use efficiency (A-C) and leaf carbon isotope ratio (D-F) at individual level. Shown are the marginal predictions (solid lines) with their 95% confidence intervals ( Ribbons), coloured by ontogenetic stage. The partial predictions show the hypothetical values when changing one predictor and keeping the others at their average value. Points show the corresponding partial residuals. Faint lines show the conditional predictions on species level. The sample size for mature trees is 54 and 100 for juvenile trees.</figcaption></figure>

overall plant water loss. For instance, genetical manipulation studies
in crops show overwhelming evidence that a reduction of SD leads to
increased WUE due to lower transpiration rates (Liu et al. 2015; Guo
et al. 2019; Li et al. 2020; Pitaloka et al. 2022). In stark contrast, there
are multiple studies that reported a positive relationship between SD
and WUE in plants (Xu et al. 2008; Naz et al. 2010; Zhao et al. 2015;
Stojnić et al. 2019; Bhaskara et al. 2022; Al-Salman et al. 2023;
Caine et al. 2023). As there is a general trade-off between GCL and
SD in plants due to space constraints of leaves (Lawson et al. 2016),
increasing GCL typically leads to lower SD in natural populations
(Haworth et al. 2023). The increase of SD and reduction of stomatal
size is a common acclimation response to water-deficit or drought
stress in trees (Dunlap and Stetter 2001; Pearce et al. 2006; Boughal-
leb et al. 2014; Stojnić et al. 2015). Gene manipulation techniques on
crops can disproportionally reduce SD compared to an increase in
GCL, which might not be realistic for natural populations, or it may

influence other factors that affect iWUE (Franks et al. 2015). In a
study by Hughes et al. (2017), the reduction of SD in barley via gene
manipulation also led to a reduction of GCL and an improved iWUE.
Therefore, the reduction of SD can have a strong positive impact on
iWUE in gene manipulation studies in crops, but the applicability of
lowering SD under field conditions, particularly in tree species, is still
not well understood. Our results show that GCL and SD are good pre-
dictors of iWUE and leaf δ¹³C across species, but GCL is more reliable
for capturing individual-level relationships and intra-specific variability
of trees.

4.3 | Specific leaf area and water-use efficiency

Specific leaf area (SLA) had a minor role in explaining water-use effi-
ciency in our study. We found that SLA had a significant negative
<figure><img src="image_5.png" /><figcaption>**FIGURE 5** Estimates of the slope parameters for water use efficiency (A) and leaf carbon isotope ratio (B) models at individual level. Shown are parameter estimates with their 95% confidence intervals. Significant differences of the slope from zero are highlighted with stars (* - *p* < 0.05, ** - *p* < 0.01, *** - *p* < 0.001). The sample size for mature trees is 54 and 100 for juvenile trees.</figcaption></figure>

impact on the individual level iWUE of mature trees and a negative impact on leaf δ¹³C of juvenile trees at the species level. SLA is widely used in functional ecology as a proxy for plant life strategies (e.g., Wright et al. 2010), where high SLA is typically associated with an ‘acquisitive’ growth strategy and high relative growth rate (Wright et al. 2004; Baird et al. 2017). SLA can reflect the differences in leaf anatomical structure that can influence the variability of iWUE between species via changes in mesophyll conductance (Mediavilla et al. 2001; Tomás et al. 2013; Carriquí et al. 2015; Trueba et al. 2022). Previous studies reported that SLA was negatively correlated with iWUE and δ¹³C in crops (Craufurd et al. 1999; Reddy et al. 2020a,b), shrubs (Horike et al. 2023), trees (Wang et al. 2013; Ge et al. 2022; Zhong et al. 2022) and forests (Guerrieri et al. 2021). Our results also show the tendency of a negative correlation between SLA and both iWUE and δ¹³C, though this was significant only for the relationship with δ¹³C of juvenile species inter-specifically and with the iWUE of mature trees intra-specifically. Our measurements showed different coverage of variable ranges for juvenile and mature species that could affect these results. The lower variability in SLA for mature trees may indicate that even though we sampled sun-exposed leaves from the crown edges, these might have been still more shaded than the sun-exposed leaves of the seedlings (Baird et al. 2017).

Moreover, leaf size increases and thickness declines vertically (Oldham et al. 2010; Schuldt et al. 2011; Coble et al. 2014). In comparison, GCL and SD are more influential and more robust traits capturing the iWUE and leaf δ¹³C variability than SLA.

## 4.4 | Relationship between intrinsic water-use efficiency and leaf carbon isotope ratio

The significant positive relationship between iWUE and leaf δ¹³C observed for both juvenile and mature tree species serves as a vital indicator of the capacity of trees in regard to carbon-water utilization. The positive relationship between gas-exchange derived iWUE and leaf δ¹³C (or negative relationship between iWUE and δ¹³C) has also been observed inter-specifically (Grossnickle et al. 2005; Ducrey et al. 2008; Roussel et al. 2009; Marguerit et al. 2014; Kaluthota et al. 2015). The leaf δ¹³C reliably reflects seasonal iWUE and therefore can capture long-term trends as in our study, where the trees were not exposed to water-deficit stress. Exposure of plants to short-term drought or heat stress can create a discrepancy between momentary iWUE and leaf δ¹³C as the sampled leaves contain carbohydrates from pre-stress period not affected by current A/gs balance (Camarero et al. 2023; Pernicová et al. 2023). The leaf δ¹³C is thus a good proxy for a long-term iWUE, especially under relatively homogeneous environmental conditions. Also, as it can be easily sampled in a large number of individuals in the field while representing plant long-term trends in water-use efficiency, the leaf δ¹³C offers good insights to analyse the adaptation of tree species to environmental aridity (Rabarijaona et al. 2022).

## 4.5 | General comparison of species and ontogenetical stages

The inter-specific differences between stomatal and leaf traits, iWUE and δ¹³C reflect their functional adaptation to the environment. We can see a clear differentiation between pioneering species such as *Betula populifolia* (low iWUE), fast-growing species such as *Populus grandidentata* (low iWUE) and climax forest species such as *Quercus petraea* or *Tilia cordata* (high iWUE). Nevertheless, our results show that there are also intermediaries between these two edge cases, where high iWUE species can also have relatively high assimilation rates (*Acer saccharinum*), or low iWUE species can have relatively low assimilation rates (*Prunus pensylvanica*). It should be noted that forest tree species typically have a high intra-specific variability, and sample size of 7–10 trees may be inefficient in capturing the functional differences between species. We observed a very high variability of GCL and SD between the species as well. The species-level GCL correlated negatively with SD, consistent with the assumed trade-off between the size and frequency to optimize the overall conductive surface to water vapour and CO₂ that was described in numerous other studies (Doheny-Adams et al. 2012; Boer et al. 2016; Rahman et al. 2022). The differences between the species we report here represent the
carbon-water balance under well-watered conditions and should be without the impact of reduced stomatal conductance. Hence, we excluded any drought stress impacts that can strongly alter the iWUE/δ¹³C of plants (Roman et al. 2015; Hajíčková et al. 2021; Hartmann et al. 2021; Gebauer et al. 2022). Therefore, the relationship between GCL and iWUE/δ¹³C could be even more (or less) pronounced under drought stress conditions.

The tree age class can also affect the iWUE, which is usually species-specific and tied to the stand structure (Tanaka-Oda et al. 2010; Matoušková et al. 2022). Neither juvenile nor mature trees in our study were light-limited; therefore, we can eliminate the impact of light competition. The only species sampled in both ontogenetical stages was Quercus rubra (QURU). The juvenile QURU had significantly higher SLA and SD than mature QURU, and significantly lower A and gs, but there were no significant differences in GCL, iWUE or δ¹³C. Similarly, a study by Cavender-Bares & Bazzaz (2000) found no changes in iWUE between three ontogenetical stages of Q. rubra under well-watered conditions. Ontogeny had a significant impact on leaf anatomical and morphological traits, but no impact on assimilation or stomatal conductance among tropical tree species (Ishida et al. 2005; Fortunel et al. 2019). These results suggest that leaf morphological traits might change during ontogenetical stages, but the water-use efficiency remains stable. Nevertheless, our sampling did not cover very old trees in which the iWUE could be limited by soil nutrients (N, P) or aging (Munné-Bosch 2007; Brueck et al. 2008; Huang et al. 2016).

The strength and significance of relationships between SD, SLA and iWUE, δ¹³C differed between ontogenetical stages (juvenile, mature). Irrespective of tree age and species, GCL showed over all a consistent negative relationship with iWUE and was significant for both ontogenetical stages inter-specifically and intra-specifically. This indicates the potential of GCL as a highly effective predictor of iWUE regardless of the ontogenetical stage. The relationship between GCL and δ¹³C was significant for both ontogenetic stages across species, but only for juvenile trees intra-specifically. The study by Fortunel et al. (2019) found a significant impact of the ontogenetical stage on leaf δ¹³C and dark respiration but not on assimilation or stomatal conductance and, therefore, probably no impact on iWUE. The lower explanatory power of GCL in regards to δ¹³C (compared to iWUE) in mature trees could be explained by differences in the respiratory substrate used throughout the season (Salomón et al. 2023). The iWUE signal recorded in the δ¹³C of plant organic material is photosynthetic rate weighted, meaning that more carbon is assimilated during periods of high photosynthetic rate. Consequently, the iWUE signal from these periods is more strongly represented in the bulk leaf material (Bing et al. 2022). This also implies that δ¹³C is more biased toward variations in A as well as tissue growth, while GCL primarily reflects the gs component of iWUE. This difference could explain why we observed stronger correlations between GCL and iWUE compared to δ¹³C. Therefore, it is critical to explore if the connections between morphological and physiological traits are consistent throughout ontogenetical development (life stages) if we want to transfer inferences

obtained at seedling or juvenile level to mature trees. Finally, our study used two sets of trees grown under different conditions and experienced varying environments during the sampling period. It is thus possible that the differences observed between juvenile and adult stages may also be driven by variations in soil type, nutrients, climate, watering status, as well as within-species genetic variation. Controlled condition experiments limiting environmental variations will now be needed if we are to characterize more precisely the sole effects of ontogeny on the relationships among SD, SLA, iWUE and δ¹³C.

## 5 | CONCLUSION

Our study confirmed our assumption that stomatal guard cell length (GCL) and stomatal density (SD) are important determinants of both short-term intrinsic water-use efficiency (iWUE) from gas exchange and long-term WUE derived from leaf carbon isotopes (δ¹³C). Both iWUE and δ¹³C correlated positively with SD and negatively with GCL for juvenile and mature trees across species. The GCL was a stronger predictor of both iWUE and δ¹³C compared to SD within species. In addition, the short-term iWUE showed a strong positive correlation with leaf δ¹³C in both ontogenetical stages. We conclude that GCL is a valuable addition to the functional trait toolkit that permits rapid phenotyping of the WUE strategy of broadleaved tree species regardless of their age class.

### AUTHOR CONTRIBUTIONS

PP, RML conceived the paper idea; PP, APP, LJL, PAW conducted the measurements; PP, RML, VM conducted the statistical analysis; PP, RML prepared the visualizations; PP, APP, LJL, RML, NKR, BS, VM wrote the first draft of the paper; BS and VM supervised all processes; all authors contributed to the final version of the paper.

### ACKNOWLEDGEMENTS

We thank Romane Hubert and Vincent Paul Riedel for their technical assistance.

### FUNDING INFORMATION

NKR acknowledges funding by the Helmholtz Initiative and Networking fund (grant no. W2/W3-156). The authors further gratefully acknowledge the financial support granted by the Bundesministerium für Ernährung und Landwirtschaft (Germany), Bundesministerium für Umwelt, Naturschutz und nukleare Sicherheit (Germany) and the Fachagentur Nachwachsende Rohstoffe eV (Germany) within the frame of the ‘Waldklimafond’ (project NONNATIVE) that partly funded this study.

### DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.
## ORCID

Peter Petrik https://orcid.org/0000-0002-1092-3031

Anja Petek-Petrik https://orcid.org/0000-0003-0463-5049

Laurent J. Lamarque https://orcid.org/0000-0002-1430-5193

Roman M. Link https://orcid.org/0000-0003-0588-3757

Pierre-André Waite https://orcid.org/0000-0003-2606-4304

Nadine K. Ruehr https://orcid.org/0000-0001-5989-7463

Bernhard Schuldt https://orcid.org/0000-0003-4738-5289

Vincent Maire https://orcid.org/0000-0002-3245-2568

## REFERENCES

Al-Salman Y, Cano FJ, Mace E, Jordan D, Groszmann M, Ghannoum O (2024) High water use efficiency due to maintenance of photosynthetic capacity in sorghum under water stress. *Journal of Experimental Botany* erae418

Al-Salman Y, Ghannoum O, Cano FJ (2023) Midday water use efficiency in sorghum is linked to faster stomatal closure rate, lower stomatal aperture and higher stomatal density. *The Plant Journal* 115: 1661–1676

Andrade MT, Oliveira LA, Pereira TS, Cardoso AA, Batista-Silva W, DaMatta FM, Zsögön A, Martins SCV (2022) Impaired auxin signaling increases vein and stomatal density but reduces hydraulic efficiency and ultimately net photosynthesis. *Journal of Experimental Botany* 73: 4147–4156

Amitrano C, Rouphael Y, Pannico A, De Pascale S, De Micco V (2021) Reducing the Evaporative Demand Improves Photosynthesis and Water-use efficiency of Indoor Cultivated Lettuce. *Agronomy* 11: 1396

Baird AS, Anderegg LDL, Lacey ME, HilleRisLambers J, Van Volkenburgh E (2017) Comparative leaf growth strategies in response to low-water and low-light availability: variation in leaf physiology underlies variation in leaf mass per area in *Populus tremuloides*. *Tree Physiology* 37: 1140–1150

Bartoń (2023) MuMln: Multi-Model Inference. 1.47.5

Bates D, Mächler M, Bolker B, Walker S (2015) Fitting Linear Mixed-Effects Models Using lme4. *J Stat Soft* 67:

Bhaskara GB, Lasky JR, Razzaque S, Zhang L, Haque T, Bonnette JE, Civelek GZ, Verslues PE, Juenger TE (2022) Natural variation identifies new effectors of water-use efficiency in *Arabidopsis*. *Proc Natl Acad Sci USA* 119: e2205305119

Bing X, Fang K, Gong X, Wang W, Xu C, Li M, Ruan C, Ma W, Li Y, Zhou F (2022) The intra-annual intrinsic water use efficiency dynamics based on an improved model. *Climatic Change* 172: 16

Boer HJ, Price CA, Wagner-Cremer F, Dekker SC, Franks PJ, Veneklaas EJ (2016) Optimal allocation of leaf epidermal area for gas exchange. *New Phytol* 210: 1219–1228

Boughalleb F, Abdellaoui R, Ben-Brahim N, Neffati M (2014) Anatomical adaptations of *Astragalus gombiformis* Pomel. under drought stress. *Open Life Sciences* 9: 1215–1225

Brendel O (2021) The relationship between plant growth and water consumption: a history from the classical four elements to modern stable isotopes. *Annals of Forest Science* 78: 47

Brueck H (2008) Effects of nitrogen supply on water-use efficiency of higher plants. *Z Pflanzenernähr Bodenk* 171: 210–219

Bucher SF, Auerswald K, Tautenhahn S, Geiger A, Otto J, Müller A, Römermann C (2016) Inter- and intraspecific variation in stomatal pore area index along elevational gradients and its relation to leaf functional traits. *Plant Ecol* 217: 229–240

Buckley TN, Warren CR (2014) The role of mesophyll conductance in the economics of nitrogen and water use in photosynthesis. *Photosynth Res* 119: 77–88

Caine RS, Harrison EL, Sloan J, Flis PM, Fischer S, Khan MS, Nguyen PT, Nguyen LT, Gray JE, Croft H (2023) The influences of stomatal size and density on rice abiotic stress resilience. *New Phytologist* 237: 2180–2195

Camarero JJ, Colangelo M, Rodríguez-González PM (2023) Tree growth, wood anatomy and carbon and oxygen isotopes responses to drought in Mediterranean riparian forests. *Forest Ecology and Management* 529: 120710

Cao X, Jia JB, Li H, Li MC, Luo J, Liang ZS, Liu TX, Liu WG, Peng CH, Luo ZB (2012) Photosynthesis, water use efficiency and stable carbon isotope composition are associated with anatomical properties of leaf and xylem in six poplar species. *Plant Biology* 14: 612–620

Cardoso AA, Gori A, Da-Silva CJ, Brunetti C (2020) Abscisic Acid Biosynthesis and Signaling in Plants: Key Targets to Improve Water Use Efficiency and Drought Tolerance. *Applied Sciences* 10: 6322

Carriquí M, Cabrera HM, Conesa MÀ, Coopman RE, Douthe C, Gago J, Gallé A, Galmés J, Ribas-Carbo M, Tomás M, Flexas J (2015) Diffusional limitations explain the lower photosynthetic capacity of ferns as compared with angiosperms in a common garden study: Photosynthetic comparison in ferns and angiosperms. *Plant Cell Environ* 38: 448–460

Casado-García A, del-Canto A, Sanz-Saez A, Pérez-López U, Bilbao-Kareaga A, Fritschi FB, Miranda-Apodaca J, Muñoz-Rueda A, Sillero-Martínez A, Yoldi-Achalandabaso A, Lacuesta M, Heras J (2020) LabelStoma: A tool for stomata detection based on the YOLO algorithm. *Computers and Electronics in Agriculture* 178: 105751

Cavender-Bares J, Bazzaz FA (2000) Changes in drought response strategies with ontogeny in *Quercus rubra*: implications for scaling from seedlings to mature trees. *Oecologia* 124: 8–18

Coble AP, Cavaleri MA (2014) Light drives vertical gradients of leaf morphology in a sugar maple (*Acer saccharum*) forest. *Tree Physiology* 34: 146–158

Craufurd PQ, Wheeler TR, Ellis RH, Summerfield RJ, Williams JH (1999) Effect of Temperature and Water Deficit on Water-Use Efficiency, Carbon Isotope Discrimination, and Specific Leaf Area in Peanut. *Crop Science* 39: 136–142

Cregg BM, Olivas-García JM, Hennessey TC (2000) Provenance variation in carbon isotope discrimination of mature ponderosa pine trees at two locations in the Great Plains. *Can J For Res* 30: 428–439

De Souza AP (2023) Dynamic responses of carbon assimilation and stomatal conductance in the future climate. *Journal of Experimental Botany* 74: 2790–2793

Dillen SY, Marron N, Koch B, Ceulemans R (2008) Genetic Variation of Stomatal Traits and Carbon Isotope Discrimination in Two Hybrid Poplar Families (*Populus deltoides* 'S9-2' × *P. nigra* 'Ghoy' and *P. deltoides* 'S9-2' × *P. trichocarpa* 'V24'). *Annals of Botany* 102: 399–407

Doheny-Adams T, Hunt L, Franks PJ, Beerling DJ, Gray JE (2012) Genetic manipulation of stomatal density influences stomatal size, plant growth and tolerance to restricted water supply across a growth carbon dioxide gradient. *Phil Trans R Soc B* 367: 547–555

Drake PL, Froend RH, Franks PJ (2013) Smaller, faster stomata: scaling of stomatal size, rate of response, and stomatal conductance. *Journal of Experimental Botany* 64: 495–505

Driesen E, De Proft M, Saeys W (2023) Drought stress triggers alterations of adaxial and abaxial stomatal development in basil leaves increasing water-use efficiency. *Horticulture Research* 10: uhad075

Dubey R, Pandey BK, Sawant SV, Shirke PA (2023) Drought stress inhibits stomatal development to improve water-use efficiency in cotton. *Acta Physiol Plant* 45: 30

Ducrey M, Huc R, Ladjal M, Guehl J-M (2008) Variability in growth, carbon isotope composition, leaf gas exchange and hydraulic traits in the eastern Mediterranean *cedars Cedrus libani* and *C. brevifolia*. *Tree Physiology* 28: 689–701

Dunlap JM, Stettler RF (2001) Variation in leaf epidermal and stomatal traits of *Populus trichocarpa* from two transects across the Washington Cascades. *Can J Bot* 79: 528–536

Durand M, Brendel O, Buré C, Le Thiec D (2019) Altered stomatal dynamics induced by changes in irradiance and vapour-pressure deficit under drought: impacts on the whole-plant transpiration efficiency of poplar genotypes. *New Phytol* 222: 1789–1802
Durand M, Brendel O, Buré C, Le Thiec D (2020) Changes in irradiance and vapour pressure deficit under drought induce distinct stomatal dynamics between glasshouse and field-grown poplars. *New Phytologist* 227: 392–406

Eckardt NA, Ainsworth EA, Bahuguna RN, Broadley MR, Busch W, Carpita NC, Castrillo G, Chory J, DeHaan LR, Duarte CM, Henry A, Jagadish SVK, Langdale JA, Leakey ADB, Liao JC, Lu K-J, McCann MC, McKay JK, Odeny DA, Jorge de Oliveira E, Platten JD, Rabbi I, Rim EY, Ronald PC, Salt DE, Shigenaga AM, Wang E, Wolfe M, Zhang X (2023) Climate change challenges, plant science solutions. *The Plant Cell* 35: 24–66

Ehleringer JR, Driscoll AW (2022) Intrinsic water-use efficiency influences establishment in Encelia farinosa. *Oecologia* 199: 563–578

Fanourakis D, Giday H, Milla R, Pieruschka R, Kjaer KH, Bolger M, Vasilevski A, Nunes-Nesi A, Fiorani F, Ottosen C-O (2015) Pore size regulates operating stomatal conductance, while stomatal densities drive the partitioning of conductance between leaf sides. *Annals of Botany* 115: 555–565

Farquhar GD, Ehleringer JR, Hubick KT (1989) Carbon Isotope Discrimination and Photosynthesis. *Annu Rev Plant Physiol Plant Mol Biol* 40: 503–537

Fortunel C, Stahl C, Heuret P, Nicolini E, Baraloto C (2019) Disentangling the effects of environment and ontogeny on tree functional dimensions for congeneric species in tropical forests. *New Phytol* 226: 385–395

Franks PJ, Beerling DJ (2009) Maximum leaf conductance driven by CO2 effects on stomatal size and density over geologic time. *Proc Natl Acad Sci USA* 106: 20343–20347

Franks PJ, W. Doheny-Adams T, Britton-Harper ZJ, Gray JE (2015) Increasing water-use efficiency directly through genetic manipulation of stomatal density. *New Phytol* 207: 188–195

Ge Z, Man X, Cai T, Duan B, Xiao R, Xu Z (2022) Environmental Factors at Different Canopy Heights Had Significant Effects on Leaf Water-Use Efficiency in Cold-Temperate Larch Forest. *Sustainability* 14: 5126

Gebauer R, Urban J, Volařík D, Matoušková M, Vitásek R, Houšková K, Hurt V, Pantová P, Polívková T, Plichta R (2022) Does leaf gas exchange correlate with petiole xylem structural traits in *Ulmus laevis* seedlings under well-watered and drought stress conditions? *Tree Physiology* 42: 2534–2545

Grossiord C, Buckley TN, Cernusak LA, Novick KA, Poulter B, Siegwolf RTW, Sperry JS, McDowell NG (2020) Plant responses to rising vapor pressure deficit. *New Phytologist* 226: 1550–1566

Grossnickle SC, Fan S, Russell JH (2005) Variation in gas exchange and water use efficiency patterns among populations of western redcedar. *Trees* 19: 32–42

Guerrieri R, Correia M, Martín-Forés I, Alfaro-Sánchez R, Pino J, Hampe A, Valladares F, Espelta JM (2021) Land-use legacies influence tree water-use efficiency and nitrogen availability in recently established European forests. *Functional Ecology* 35: 1325–1340

Guo X, Wang Y, Zhao P, Xu P, Yu G, Zhang L, Xiong Y, Xiang C (2019) AtEDT1/HDG11 regulates stomatal density and water-use efficiency via ERECTA and E2Fa. *New Phytologist* 223: 1478–1488

Hájičková M, Plichta R, Urban J, Volařík D, Gebauer R (2021) Low resistance but high resilience to drought of flushing Norway spruce seedlings. *Tree Physiology* 41: 1848–1860

Haman J, Avery M (2017) ciTools: Confidence or Prediction Intervals, Quantiles, and Probabilities for Statistical Models. 0.6.1

Hartmann H, Link RM, Schuldt B (2021) A whole-plant perspective of isohydry: stem-level support for leaf-level plant water regulation. *Tree Physiology* 41: 901–905

Haworth M, Marino G, Loreto F, Centritto M (2021) Integrating stomatal physiology and morphology: evolution of stomatal control and development of future crops. *Oecologia* 197: 867–883

Haworth M, Marino G, Materassi A, Raschi A, Scutt CP, Centritto M (2023) The functional significance of the stomatal size to density relationship: Interaction with atmospheric [CO2] and role in plant physiological behaviour. *Science of The Total Environment* 863: 160908

Homeier J, Seeler T, Pierick K, Leuschner C (2021) Leaf trait variation in species-rich tropical Andean forests. *Sci Rep* 11: 9993

Horike H, Kinoshita T, Kume A, Hanba YT (2023) Responses of leaf photosynthetic traits, water-use efficiency, and water relations in five urban shrub tree species under drought stress and recovery. *Trees* 37: 53–67

Huang G, Yang Y, Zhu L, Ren X, Peng S, Li Y (2022) The structural correlations and the physiological functions of stomatal morphology and leaf structures in C3 annual crops. *Planta* 256: 39

Huang Z, Liu B, Davis M, Sardans J, Peñuelas J, Billings S (2016) Long-term nitrogen deposition linked to reduced water use efficiency in forests with low phosphorus availability. *New Phytologist* 210: 431–442

Hughes J, Hepworth C, Dutton C, Dunn JA, Hunt L, Stephens J, Waugh R, Cameron DD, Gray JE (2017) Reducing Stomatal Density in Barley Improves Drought Tolerance without Impacting on Yield. *Plant Physiol* 174: 776–787

Impa SM, Nadaradjan S, Boominathan P, Shashidhar G, Bindumadhava H, Sheshayee MS (2005) Carbon Isotope Discrimination Accurately Reflects Variability in WUE Measured at a Whole Plant Level in Rice. *Crop Science* 45: 2517–2522

Isasa E, Link RM, Jansen S, Tezeh FR, Kaack L, Sarmento Cabral J, Schuldt B (2023) Addressing controversies in the xylem embolism resistance-vessel diameter relationship. *New Phytologist* 238: 283–296

Ishida A, Yazaki K, Hoe AL (2005) Ontogenetic transition of leaf physiology and anatomy from seedlings to mature trees of a rain forest pioneer tree, *Macaranga gigantea*. *Tree Physiology* 25: 513–522

Jiao P, Liang Y, Chen S, Yuan Y, Chen Y, Hu H (2023) Bna.EPF2 Enhances Drought Tolerance by Regulating Stomatal Development and Stomatal Size in Brassica napus. *IJMS* 24: 8007

Jiao Z, Han S, Li Z, Huang M, Niu M-X, Yu X, Liu C, Wang H-L, Yin W, Xia X (2022) PdEPFL6 reduces stomatal density to improve drought tolerance in poplar. *Industrial Crops and Products* 182: 114873

Kaluthota S, Pearce DW, Evans LM, Letts MG, Whitham TG, Rood SB (2015) Higher photosynthetic capacity from higher latitude: foliar characteristics and gas exchange of southern, central and northern populations of Populus angustifolia. *Tree Physiol* 35: 936–948

Kardiman R, Ræbild A (2018) Relationship between stomatal density, size and speed of opening in Sumatran rainforest species. *Tree Physiol* 38: 696–705

Kurjak D, Petrik P, Konôpková AS, Link RM, Gömöry D, Hajek P, Liesebach M, Leuschner C, Schuldt B (2024) Inter-provenance variability and phenotypic plasticity of wood and leaf traits related to hydraulic safety and efficiency in seven European beech (Fagus sylvatica L.) provenances differing in yield. *Annals of Forest Science* 81: 11

Kuznetsova A, Brockhoff PB, Christensen RHB (2017) ImerTest Package: Tests in Linear Mixed Effects Models. *J Stat Soft* 82:

Lawson T, Blatt MR (2014) Stomatal Size, Speed, and Responsiveness Impact on Photosynthesis and Water-use efficiency. *Plant Physiology* 164: 1556–1570

Lawson T, Kramer DM, Raines CA (2012) Improving yield by exploiting mechanisms underlying natural variation of photosynthesis. *Current Opinion in Biotechnology* 23: 215–220

Lawson T, McElwain JC (2016) Evolutionary trade-offs in stomatal spacing. *New Phytol* 210: 1149–1151

Leakey ADB, Ferguson JN, Pignon CP, Wu A, Jin Z, Hammer GL, Lobell DB (2019) Water Use Efficiency as a Constraint and Target for Improving the Resilience and Productivity of C 3 and C 4 Crops. *Annu Rev Plant Biol* 70: 781–808

Lei Z, He Y, Li X, He Z, Zhang Y, Zhang W, Liu F, Zhang Y (2023) Domestication has reduced leaf water-use efficiency associated with the anatomy of abaxial stomata in cotton. *Journal of Experimental Botany* 74: 878–888

Li S, Zhang J, Liu L, Wang Z, Li Y, Guo L, Li Y, Zhang X, Ren S, Zhao B, Zhang N, Guo Y (2020) SITLFP8 reduces water loss to improve water-use efficiency by modulating cell size and stomatal density via endoreplication. *Plant Cell Environ* 43: 2666–2679
Li Y, Li H, Li Y, Zhang S (2017) Improving water-use efficiency by decreasing stomatal conductance and transpiration rate to maintain higher ear photosynthetic rate in drought-resistant wheat. *The Crop Journal* 5: 231–239

Link, R.M., 2020. corrmorant: Flexible Correlation Matrices Based on 'ggplot2'. R package version 0.0.0.9007. URL: http://github.com/r-link/corrmorant [accessed 2023-11-29]

Liu C, He N, Zhang J, Li Y, Wang Q, Sack L, Yu G (2018) Variation of stomatal traits from cold temperate to tropical forests and association with water use efficiency. *Functional Ecology* 32: 20–28

Liu C, Sack L, Li Y, Zhang J, Yu K, Zhang Q, He N, Yu G (2023) Relationships of stomatal morphology to the environment across plant communities. *Nat Commun* 14: 6629

Liu F, Yang W, Wang Z, Xu Z, Liu H, Zhang M, Liu Y, An S, Sun S (2010) Plant size effects on the relationships among specific leaf area, leaf nutrient content, and photosynthetic capacity in tropical woody species. *Acta Oecologica* 36: 149–159. https://doi.org/10.1016/j.actao. 2009.11.004

Liu Q, Wang Z, Yu S, Li W, Zhang M, Yang J, Li D, Yang J, Li C (2021) Pu-miR172d regulates stomatal density and water-use efficiency via targeting PuGTL1 in poplar. *Journal of Experimental Botany* 72: 1370– 1383

Liu Y, Qin L, Han L, Xiang Y, Zhao D (2015) Overexpression of maize SDD1 (ZmSDD1) improves drought resistance in Zea mays L. by reducing stomatal density. *Plant Cell Tiss Organ Cult* 122: 147–159

Ma WT, Yu YZ, Wang X, Gong XY (2023) Estimation of intrinsic water-use efficiency from δ13C signature of C3 leaves: Assumptions and uncertainty. *Front Plant Sci* 13: 1037972

Matoušková M, Urban J, Volařík D, Hájičková M, Matula R (2022) Cop-picing modulates physiological responses of sessile oak (Quercus petreae Matt. Lieb.) to drought. *Forest Ecology and Management* 517: 120253

Marguerit E, Bouffier L, Chancerel E, Costa P, Lagane F, Guehl J-M, Plomion C, Brendel O (2014) The genetics of water-use efficiency and its relation to growth in maritime pine. *Journal of Experimental Botany* 65: 4757–4768

McAusland L, Vialet-Chabrand S, Davey P, Baker NR, Brendel O, Lawson T (2016) Effects of kinetics of light-induced stomatal responses on photosynthesis and water-use efficiency. *New Phytol* 211: 1209–1220

Mediavilla S, Escudero A, Heilmeier H (2001) Internal leaf anatomy and photosynthetic resource-use efficiency: interspecific and intraspecific comparisons. *Tree Physiology* 21: 251–259

Mohammed U, Caine RS, Atkinson JA, Harrison EL, Wells D, Chater CC, Gray JE, Swarup R, Murchie EH (2019) Rice plants overexpressing OsEPF1 show reduced stomatal density and increased root cortical aerenchyma formation. *Sci Rep* 9: 5584

Munné-Bosch S (2007) Aging in Perennials. *Critical Reviews in Plant Sciences* 26: 123–138

Naz N, Hameed M, Ashraf M, Al-Qurainy F, Arshad M (2010) Relationships between gas-exchange characteristics and stomatal structural modifications in some desert grasses under high salinity. *Photosynt* 48: 446–456

Nakagawa S, Johnson PCD, Schielzeth H (2017) The coefficient of determination R 2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded. *J R Soc Interface* 14: 20170213

Nguyen TB-A, Lefoulon C, Nguyen T-H, Blatt MR, Carroll W (2023) Engineering stomata for enhanced carbon capture and water-use efficiency. *Trends in Plant Science* 28: 1290–1309

Oldham AR, Sillett SC, Tomescu AMF, Koch GW (2010) The hydrostatic gradient, not light availability, drives height-related variation in *Sequoia sempervirens* (Cupressaceae) leaf anatomy. *American J of Botany* 97: 1087–1097

Ozeki K, Miyazawa Y, Sugiura D (2022) Rapid stomatal closure contributes to higher water-use efficiency in major C4 compared to C3 Poaceae crops. *Plant Physiology* 189: 188–203

Pearce DW, Millard S, Bray DF, Rood SB (2006) Stomatal characteristics of riparian poplar species in a semi-arid environment. *Tree Physiology* 26: 211–218

Petek-Petrik A, Húdoková H, Fleischer P, Jamnická G, Kurjak D, Sliacka Konšípková A, Petrik P (2023) The combined effect of branch position, temperature, and VPD on gas exchange and water-use efficiency of Norway spruce. *Biologia plant* 67: 136–141

Pernicová N, Hlaváčová M, Findurová H, Čáslavský J, Urban O, Klem K, Trnka M (2023) Grain carbon isotopes indicate the ability of wheat plants to maintain enhanced intrinsic water-use efficiency even after short-term exposure to high temperatures and drought. *Plant Physiology and Biochemistry* 205: 108155

Paillassa J, Wright IJ, Prentice IC, Pepin S, Smith NG, Ethier G, Westerband AC, Lamarque LJ, Wang H, Cornwell WK, Maire V (2020) When and where soil is important to modify the carbon and water economy of leaves. *New Phytol* 228: 121–135

Pan S, Wang X, Yan Z, Wu J, Guo L, Peng Z, Wu Y, Li J, Wang B, Su Y, Liu L (2024) Leaf stomatal configuration and photosynthetic traits jointly affect leaf water use efficiency in forests along climate gradients. *New Phytologist* nph.20100

Petek-Petrik A, Petrik P, Halmová M, Plichta R, Matoušková M, Houšková K, Chudomelová M, Urban J, Hedl R (2024) Comparison of morphological and physiological response to drought stress among temperate forest understory forbs and graminoids. doi.org/https://doi.org/10.1101/2024.10.01.615773

Petrik P, Fleischer P, Tomes J, Pichler V, Fleischer P (2024) Post-windthrow differences of carbon and water fluxes between managed and unmanaged Norway spruce stands. *Agricultural and Forest Meteorology* 355: 110102

Petrik P, Petek A, Konšípková A, Bosela M, Fleischer P, Frýdl J, Kurjak D (2020) Stomatal and Leaf Morphology Response of European Beech (Fagus sylvatica L.) Provenances Transferred to Contrasting Climatic Conditions. *Forests* 11: 1359

Petrik P, Petek-Petrik A, Mukarram M, Schuldt B, Lamarque LJ (2023) Leaf physiological and morphological constraints of water-use efficiency in C3 plants. *AoB PLANTS* 15: plad047

Petrik P, Petek-Petrik A, Kurjak D, Mukarram M, Klein T, Gömöry D, Střelcová K, Frýdl J, Konšípková A (2022) Interannual adjustments in stomatal and leaf morphological traits of European beech (Fagus sylvatica L.) demonstrate its climate change acclimation potential. *Plant Biol* J 24: 1287–1296

Pitaloka MK, Caine RS, Hepworth C, Harrison EL, Sloan J, Chutteang C, Phunthong C, Nongngok R, Toojinda T, Ruengphayak S, Arikit S, Gray JE, Vanavichit A (2022) Induced Genetic Variations in Stomatal Density and Size of Rice Strongly Affects Water-use efficiency and Responses to Drought Stresses. *Front Plant Sci* 13: 801706

Pollet TV, Stulp G, Henzi SP, Barrett L (2015) Taking the aggravation out of data aggregation: A conceptual guide to dealing with statistical issues related to the pooling of individual-level observational data. *American J Primate* 77: 727–740

Puchi PF, Dalmorech D, Vangi E, Battipaglia G, Tognetti R, Collalti A (2024) Contrasting patterns of water use efficiency and annual radial growth among European beech forests along the Italian peninsula. *Sci Rep* 14: 6526

Rabarijaona A, Ponton S, Bert D, Ducoussou A, Richard B, Levillain J, Brendel O (2022) Provenance Differences in Water-Use Efficiency Among Sessile Oak Populations Grown in a Mesic Common Garden. *Front For Glob Change* 5: 914199

Rahman AA-NS, Rahman M, Shimanto MH, Kibria MG, Islam M (2022) Stomatal size and density trade-off varies with leaf phenology and species shade tolerance in a South Asian moist tropical forest. *Funct Plant Biol* 49: 307–318

Reddy SH, Da Costa MVJ, Kambalimath SK, Rajanna Mavinahalli P, Muthurajan R, Chinnusamy V, Sevanthi AM, Neelamraju S, Gopala Krishnan S, Singh AK, Singh NK, Sharma RP, Pathappa N, Sreeman SM
(2020a) Relative contribution of stomatal parameters in influencing WUE among rice mutants differing in leaf mass area. *Plant Physiol Rep* 25: 483–495

Reddy SH, Singhal RK, DaCosta MVJ, Kambalimath SK, Rajanna MP, Muthurajan R, Sevanthi AM, Mohapatra T, Sarla N, Chinnusamy V, S GK, Singh AK, Singh NK, Sharma RP, Pathappa N, Sheshayee SM (2020b) Leaf mass area determines water-use efficiency through its influence on carbon gain in rice mutants. *Physiol Plantarum* 169: 194–213

Robertson BC, He T, Li C (2021) The Genetic Control of Stomatal Development in Barley: New Solutions for Enhanced Water-Use Efficiency in Drought-Prone Environments. *Agronomy* 11: 1670

Roman DT, Novick KA, Brzostek ER, Dragoni D, Rahman F, Phillips RP (2015) The role of isohydric and anisohydric species in determining ecosystem-scale response to severe drought. *Oecologia* 179: 641–654

Roussel M, Le Thiec D, Montpied P, Ningre N, Guehl J-M, Brendel O (2009) Diversity of water use efficiency among Quercus robur genotypes: contribution of related leaf traits. *Ann For Sci* 66: 408–408

Salomón RL, Rodriguez-Calcerrada J, De Roo L, Miranda JC, Bodé S, Boeckx P, Steppe K (2023) Carbon isotope composition of respired CO2 in woody stems and leafy shoots of three tree species along the growing season: physiological drivers for respiratory fractionation. *Tree Physiol* 43: 1731–1744

Schneider CA, Rasband WS, Eliceiri KW (2012) NIH Image to ImageJ: 25 years of image analysis. *Nat Methods* 9: 671–675

Schuldt B, Leuschner C, Horna V, Moser G, Köhler M, van Straaten O, Barus H (2011) Change in hydraulic properties and leaf traits in a tall rainforest tree species subjected to long-term throughfall exclusion in the perhumid tropics. *Biogeosciences* 8: 2179–2194

Stojnić S, Kovačević B, Kebert M, Vaštag E, Bojović M, Stanković-Nedić M, Orlović S (2019) The use of physiological, biochemical and morpho-anatomical traits in tree breeding for improved water-use efficiency of *Quercus robur* L. *Forest Syst* 28: e017

Stojnić S, Orlović S, Miljković D, Galić Z, Kebert M, von Wuehlisch G (2015) Provenance plasticity of European beech leaf traits under differing environmental conditions at two Serbian common garden sites. *Eur J Forest Res* 134: 1109–1125

Tanaka Y, Sugano SS, Shimada T, Hara-Nishimura I (2013) Enhancement of leaf photosynthetic capacity through increased stomatal density in Arabidopsis. *New Phytol* 198: 757–764

Tanaka-Oda A, Kenzo T, Koretsune S, Sasaki H, Fukuda K (2010) Ontogenetic changes in water-use efficiency (613C) and leaf traits differ among tree species growing in a semiarid region of the Loess Plateau, China. *Forest Ecology and Management* 259: 953–957

Tian M, Yu G, He N, Hou J (2016) Leaf morphological and anatomical traits from tropical to temperate coniferous forests: Mechanisms and influencing factors. *Sci Rep* 6: 19703

Tomás M, Flexas J, Copolovici L, Galmés J, Hallik L, Medrano H, Ribas-Carbó M, Tosens T, Vislap V, Niinemets Ü (2013) Importance of leaf anatomy in determining mesophyll diffusion conductance to CO2 across species: quantitative limitations and scaling up by models. *Journal of Experimental Botany* 64: 2269–2281

Trueba S, Théroux-Rancourt G, Earles JM, Buckley TN, Love D, Johnson DM, Brodersen C (2022) The three-dimensional construction of leaves is coordinated with water use efficiency in conifers. *New Phytologist* 233: 851–861

Vadez V, Pilloni R, Grondin A, Hajjarpoor A, Belhouchette H, Brouziyne Y, Chehbouni G, Kharrou MH, Zitouna-Chebbi R, Mekki I, Molénat J, Jacob F, Bossuet J (2023) Water-use efficiency across scales: from genes to landscapes. *Journal of Experimental Botany* erad052

Vicente-Serrano SM, McVicar TR, Miralles DG, Yang Y, Tomas-Burguera M (2020) Unraveling the influence of atmospheric evaporative demand on drought and its response to climate change. *WIREs Clim Change* 11:

Vile D, Garnier É, Shipley B, Laurent G, Navas M-L, Roumet C, Lavorel S, Díaz S, Hodgson JG, Lloret F, Midgley GF, Poorter H, Rutherford MC, Wilson PJ, Wright IJ (2005) Specific Leaf Area and Dry Matter Content Estimate Thickness in Laminar Leaves. *Annals of Botany* 96: 1129–1136

Wang D, LeBauer D, Kling G, Voigt T, Dietze MC (2013) Ecophysiological screening of tree species for biomass production: trade-off between production and water use. *Ecosphere* 4: 1–22

Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, Lamont BB, Lee T, Lee W, Lusk C, Midgley JJ, Navas M-L, Niinemets Ü, Oleksyn J, Osada N, Poorter H, Poot P, Prior L, Pyankov VI, Roumet C, Thomas SC, Tjoelker MG, Veneklaas EJ, Villar R (2004) The worldwide leaf economics spectrum. *Nature* 428: 821–827

Wright SJ, Kitajima K, Kraft NJB, Reich PB, Wright IJ, Bunker DE, Condit R, Dalling JW, Davies SJ, Díaz S, Engelbrecht BMJ, Harms KE, Hubbell SP, Marks CO, Ruiz-Jaen MC, Salvador CM, Zanne AE (2010) Functional traits and the growth-mortality trade-off in tropical trees. *Ecology* 91: 3664–3674

Wu T-L, Chen P-Y, Du X, Wu H, Ou J-Y, Zheng P-X, Wu Y-L, Wang R-S, Hsu T-C, Lin C-Y, Lin W-Y, Chang P-L, Ho C-MK, Lin Y-C (2024) Stoma-Vision: stomatal trait analysis through deep learning. doi.org/https://doi.org/10.1101/2024.04.24.590919

Xiong Z, Xiong D, Cai D, Wang W, Cui K, Peng S, Huang J (2022) Effect of stomatal morphology on leaf photosynthetic induction under fluctuating light across diploid and tetraploid rice. *Environmental and Experimental Botany* 194: 104757

Xu Z, Zhou G (2008) Responses of leaf stomatal density to water status and its relationship with photosynthesis in a grass. *Journal of Experimental Botany* 59: 3317–3325

Zhang Z, Zhang L, Xu H, Creed IF, Blanco JA, Wei X, Sun G, Asbjornsen H, Bishop K (2023) Forest water-use efficiency: Effects of climate change and management on the coupling of carbon and water processes. *Forest Ecology and Management* 534: 120853

Zhao W, Sun Y, Kjelgren R, Liu X (2015) Response of stomatal density and bound gas exchange in leaves of maize to soil water deficit. *Acta Physiol Plant* 37: 1704

Zhong G, Tian Y, Liu P, Jia X, Zha T (2022) Leaf Traits and Resource Use Efficiencies of 19 Woody Plant Species in a Plantation in Fangshan, Beijing, China. *Forests* 14: 63

## SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

**How to cite this article:** Petrik, P., Petek-Petrik, A., Lamarque, L.J., Link, R.M., Waite, P.-A., Ruehr, N.K. et al. (2024) Linking stomatal size and density to water use efficiency and leaf carbon isotope ratio in juvenile and mature trees. *Physiologia Plantarum*, 176(6), e14619. Available from: https://doi.org/10.1111/ppl.14619