# Tree aging does not affect the ranking for water use efficiency recorded from δ13C in three Populus deltoides x P. nigra genotypes

Fahad Rasheed, Erwin Dreyer, D. Le Thiec, Zikria Zafar, Sylvain Delagrange

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Fahad Rasheed, Erwin Dreyer, D. Le Thiec, Zikria Zafar, Sylvain Delagrange. Tree aging does not affect the ranking for water use efficiency recorded from δ13C in three Populus deltoides x P. nigra genotypes. iForest: Biogeosciences and Forestry, 2019, 12 (3), pp.272-278. 10.3832/ifor2896-012. hal-02624170

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# Tree aging does not affect the ranking for water use efficiency recorded from δ¹³C in three *Populus deltoides* × *P. nigra* genotypes

Fahad Rasheed (1-2),
Erwin Dreyer (1-3),
Didier Le Thiec (1-3),
Zikria Zafar (2),
Sylvain Delagrange (4)

A large variability of water use efficiency (assessed from the carbon isotopic discrimination in leaves and leaf soluble sugars) has been detected among poplar genotypes. Checking whether such differences detected in young trees (1-2 years old) remain stable with tree age is a prerequisite to use this trait with confidence for breeding purposes. In this study, a synchronic approach was used to test the age-related stability of the genotypic ranking of carbon isotopic discrimination in wood (Δ¹³C) until tree maturity. We sampled 376 trees between 4 and 20 years from three *Populus deltoides* × *P. nigra* genotypes growing in 41 common-garden trials across France. Carbon and nitrogen percentages along with δ¹³C was measured in the bulk wood of the year 2009 and used to compute the Δ¹³C. Basal area increment between 2008 and 2009 was also measured. Results showed that Δ¹³C increased (i.e., water use efficiency decreased) between ages 4 to 6 and remained stable later on. Significant differences among genotypes were found but the ranking among genotypes remained stable with age during the assessed life span. Furthermore, basal area increment and Δ¹³C were positively correlated interannually. This large-scale survey shows that despite crossing over in the temporal trend, water use efficiency remained stable with age across 3 poplar genotypes. However, further studies with a large number of genotypes are required to confirm whether this trait can be used to maintain or even improve productivity of poplar plantations, while lowering water consumption.

**Keywords:** Water Use Efficiency, Age, Wood, Tree Ring, *Populus* × *eurameri-cana*, Basal Area Increment, Synchronic Approach

## Introduction

In the context of climate change and fluctuating precipitation patterns (IPCC 2013), water use efficiency (WUE, ratio between biomass accumulated and water transpired) has become an interesting trait for breeding new genotypes (Condon et al. 2004, Richards et al. 2010, Vadez et al. 2014). Isotopic discrimination against ¹³C (Δ¹³C) during CO₂ diffusion through stomata and photosynthesis is an indirect indicator of intrinsic water use efficiency (iWUE, ratio between net CO₂ assimilation rate, A, and stomatal conductance to water vapour, gₐ – Farquhar & Richards 1984, Farquhar et al. 1989, Ehleringer et al. 1993). Indeed, this trait was found to be under tight genetic control in several tree species like poplar, pines, chestnut and oaks among others (Lauteri et al. 1997, Brendel et al. 2002, 2008, Rasheed et al. 2015). Furthermore, given the lack of correlation observed between WUE and productivity or, in some instances, the positive correlation between both traits (Vadez et al. 2014), selecting tree species or genotypes based on their ability to express a high WUE is desirable. Such a strategy has been explored in some crops in a context of improving water management (Condon et al. 2004, Richards et al. 2010) and might thus be particularly suitable for sustaining wood production under the incertitude of water availability.

Poplar genotypes are known to display large differences in growth performance and biomass production (Rasheed et al. 2013). A large genotypic variability of Δ¹³C was found among *Populus deltoides* × *P. nigra* genotypes in controlled environment (Marron et al. 2005) and open field experiments (Monclus et al. 2005, Dillen et al. 2008). Using direct measurements, this variability in Δ¹³C is also found tightly related to variability in the whole plant water use efficiency in *Populus deltoides* × *P. nigra* and in *Populus nigra* (Rasheed et al. 2013, 2015). Interestingly, no correlation was found between productivity and Δ¹³C (Monclus et al. 2005, Dillen et al. 2008), giving opportunity to breed for enhanced WUE without compromising productivity in poplar genotypes. Nevertheless, previous studies on poplar genotypes were conducted on seedlings of 1-2 years and there are few studies investigating the stability of genotype ranking for WUE at tree scale.

Previous studies has demonstrated that Δ¹³C (recorded from tree ring cellulose and bulk wood) is severely affected by age, usually decreasing by a 1-3 per mil with increasing tree age (Francey & Farquhar 1982, Bert et al. 1997, Duquesnay et al. 1998, McCarroll & Pawellek 2001, Brienen et al. 2017). Such an age-related effect may be related to: (i) assimilation of respired CO₂ near the forest floor which is already depleted in ¹³C (Schleser & Jayasekera

<footnote>(1) INRA, UMR1137 Ecologie et Ecophysiologie Forestières, IFR 110 EFABA, F-54280 Champenoux (France); (2) Department of Forestry & Range Management, University of Agriculture Faisalabad, P.O. Box 38000 (Pakistan); (3) Université de Lorraine, UMR1137 Ecologie et Ecophysiologie Forestières, IFR 110 EFABA, F-54500 Vandoeuvre-lès-Nancy (France); (4) Department of Natural Sciences, Institute of Temperate Forest Sciences (ISFORT), University of Quebec in Outaouais (UQO), 58 Main St, Ripon, Quebec J0V 1V0 (Canada)</footnote>

<footnote>@ Fahad Rasheed
(fahad.rasheed@uaf.edu.pk)</footnote>

<footnote>Received: Jun 15, 2018 - Accepted: Mar 18, 2019</footnote>

<footnote>**Citation:** Rasheed F, Dreyer E, Le Thiec D, Zafar Z, Delagrange S (2019). Tree aging does not affect the ranking for water use efficiency recorded from δ¹³C in three *Populus deltoides* × *P. nigra* genotypes. iForest 12: 272-278. - doi: 10.3832/ifor2896-012 [online 2019-05-21]</footnote>

<footnote>Communicated by: Rossella Guerrieri</footnote>
1985); (ii) re-assimilation of respired CO₂ re-
tained within the plant canopy (Francey &
Farquhar 1982); (iii) decreasing hydraulic
conductivity of xylem conduits with age
(Monserud & Marshall 2001); (iv) reduced
total soil-to-leaf hydraulic conductance
with tree size (McCarroll & Loader 2004);
or (v) tree height and light availability (Bri-
enen et al. 2017). Records of Δ¹³C in leaves
and phloem sap of poplars with different
ages revealed a rather stable ranking of
the genotypic differences with tree age
(Bonhomme et al. 2008). More recently,
using a diachronic approach, several geno-
types of *Populus deltoides* × *P. nigra* grow-
ing in common gardens were compared
and the effects of ageing (from 5 to 20
years) on the genotype ranking were stud-
ied using the Δ¹³C signals in tree rings as a
surrogate for WUE (Rasheed et al. 2011). In
the latter study, small changes in Δ¹³C with
tree age and no significant interaction be-
tween genotype and tree age were found,
reinforcing the pertinence of ranking geno-
types using Δ¹³C. However, in a such di-
achronic study, the influence of long-term
environmental variability and annual ef-
fects related to rainfall on Δ¹³C is assumed
similar as the sampled trees were grown in
common gardens that experienced the
same environmental conditions.

In the present study we used a synchron-

ic approach where Δ¹³C was recorded and
compared in tree rings with same forma-
tion date, but from tree of different ages
and contrasting environmental conditions.
This sampling technique was used to min-
imise long-term environment effect and
maximise age effect. Three different geno-
types of *Populus deltoides* × *P. nigra* were
used and carbon isotopic composition
(δ¹³C) of the bulk wood from the year 2009
was measured and Δ¹³C was computed.
Since cellulose and lignin are the major
components of bulk wood, and due to dif-
ferent biochemical pathways involved in
their formation, the carbon isotopic signals
of these two components are also differ-
ent, i.e., lignin is ~3% depleted than cellu-
lose (Loader et al. 2003, McCarroll & Load-
er 2004). Any variation in cellulose:lignin
ratio can potentially affect the overall δ¹³C
signals of whole wood. Therefore, the vari-
ation in carbon percentage in the whole
wood was investigated, that potentially
elucidates the variation of lignin in the bulk
wood (Lamlom & Savidge 2003). More-
over, nitrogen percentage in the bulk
wood that can give insight regarding the
tree response to the variation of available
soil nitrogen resource (Guerrieri et al. 2011,
Billings et al. 2016) was also measured.

The main difficulty of the synchronic ap-
proach is the lack of large-scale common

garden grouping a sufficient number of
genotypes with different ages. We there-
fore used 41 small common gardens (Fig. 1)
maintained in different locations in France
by the *Institut du Développement Forestier*
(IDF-CNPF) and gathered samples for three
genotypes of *Populus deltoides* × *P. nigra*.
Using this approach, we tested the hy-
potheses that: (i) water use efficiency esti-
mated from Δ¹³C in wood is affected by tree
age; and (ii) genotype ranking based on
Δ¹³C does not change with tree age.

Material and methods

The aim of this study was to evidence the
effect of age on stability of genotype rank-
ing for Δ¹³C. However, studying long-term
physiological response in trees can be
tricky because of age and environmental
signals overlapping each other. Therefore,
maximising age-related signals through ap-
propriate sampling technique becomes a
prerequisite. In this regard a synchronic
technique, where carbon isotope discrimi-
nation was compared among tree rings
with same formation date but from trees
of different ages and environments, there-
by maximising the age signal. A major con-
straint while applying such technique is to
find a large number of poplar genotypes of
different ages in a common garden. To ob-
tain a satisfying sample of trees of differ-
ent ages in different genotypes and envi-
ronments, we sampled trees across a large
number of plantations in France (Fig. 1).
These small plantations were established
by the Centre National de la Propriété For-
estière - Institut pour le Développement
Forestier (CNPF-IDF) to compare the local
performance of genotypes.

Study sites

The genotypes were planted in plots of
25 trees at a distance of 7 × 7 m, i.e., at a
density of 204 stems ha⁻¹. Forty-one sites
were selected (Fig. 1) which were located
all over France (see Tab. S1 in Supplemen-
tary material for site information and spa-
tial coordinates). Sites covered a large
range of climates with mean annual tem-
perature from 10 to 14 °C and precipitation
from 600 to 1200 mm. Sampling sites were
subsequently categorised as water avail-
able (WA, annual rainfall from 1000 to 1200
mm) or water limiting (WL, annual rainfall
from 600 to 800 mm; precipitation record
maintained by the Centre National de la
Propriété Forestière - Institut pour le Dével-
opplement Forestier, CNPF-IDF).

Sample collection and preparation

We focused on 3 *Populus deltoides* × *P. nigra* genotypes: Koster, I-214 and Dorskamp, as these genotypes are known to display contrasting Δ¹³C at leaf level (Monclus et al. 2005). Moreover, they were present in a large number of the surveyed plantations and covered the different age classes. The last annual ring corresponding to year 2009 was sampled in February 2010 with an increment borer (0.5 cm²) on ~5 trees site⁻¹

<figure><img src="image_3.png" /><figcaption>Fig. 1 - Location of 41 sampling sites across France. Each site is represented by a closed star.</figcaption></figure>
<table><caption>**Tab. 1** - Carbon and nitrogen percentage, and δ¹³C measured on the bulk wood from the year 2009 from three genotypes of Populus deltoides × P. nigra aged from 4 to 18 years. Data was analyzed using linear mixed model for the effects of genotype (G), age (A) and interaction (G × A). Table shows the mean values (± SE) combining all age classes. Different letters indicate significant genotype differences after multi-comparison test (Tukey HSD, P < 0.05).</caption><thead><tr><th rowspan="2">Variable</th><th colspan="3">Clone</th><th colspan="3">Effect (Prob.)</th></tr><tr><th><i>Dorskamp</i></th><th><i>I-214</i></th><th><i>Koster</i></th><th>G</th><th>A</th><th>G × A</th></tr></thead><tbody><tr><td>C %</td><td>46.8 ± 0.28 <sup>a</sup></td><td>47.7 ± 0.097 <sup>b</sup></td><td>47.7 ± 0.10 <sup>b</sup></td><td>&lt;0.001</td><td>0.051</td><td>0.305</td></tr><tr><td>N %</td><td>0.154 ± 0.004</td><td>0.14 ± 0.007</td><td>0.168 ± 0.007</td><td>0.248</td><td>&lt;0.001</td><td>0.734</td></tr><tr><td>Δ¹³C (‰)</td><td>20.3 ± 0.076 <sup>a</sup></td><td>19.9 ± 0.053 <sup>b</sup></td><td>19.4 ± 0.078 <sup>c</sup></td><td>&lt;0.001</td><td>&lt;0.001</td><td>&lt;0.001</td></tr><tr><td>BAI (cm² yr⁻¹)</td><td>88.4 ± 9.54</td><td>103 ± 11.0</td><td>107.3 ± 13.4</td><td>0.467</td><td>0.023</td><td>0.167</td></tr></tbody></table>

genotype¹, yielding 376 samples. All cores were divided into seven age classes, i.e., 4, 7, 9, 11, 13, 15 and 18 years. In order to minimise the environmental effect on Δ¹³C: (i) date effect was discarded as all cores corresponded to year 2009; and (ii) site effect was averaged in each age class by ensuring the representation of trees from both site types, i.e., WA and WL sites.

The ring formed in 2009 was carefully separated from the adjacent one and from bark with a sharp razor blade. After drying at 70 °C for 48h, each ring was ground separately into fine homogeneous powder using a ring grinder (SODEMI, CEP Industries Department, Cergy-Pontoise. France). One mg of the resulting wood powder was weighed in tin capsules for δ¹³C analysis.

### Carbon and nitrogen percentage and carbon isotope analysis

Wood powder was combusted at 1050 °C in sealed evacuated quartz tubes containing cobalt oxide and chromium oxide as catalyst, and an amount of pure oxygen. The gases produced during combustion, CO₂, H₂O and NOₓ were passed through a reduction tube where N₂ was produced and excess of oxygen was removed. Water was trapped by using anhydrous magnesium perchlorate and after reversible absorption, carbon and nitrogen percentages were measured in an elemental analyser (NA 1500-NC®, Carlo Erba, Milan, Italy – Rasheed et al. 2011). Finally, combusted products were separated by gas chromatography and the CO₂ was delivered to an isotope ratio mass spectrometer (DeltaS®, Finnigan, Bremen, Germany). Carbon isotope composition was expressed as δ¹³C (eqn. 1):

$$ \delta^{13}C = (R_{sample} / R_{standard} - 1) \cdot 1000 \quad (1) $$

where Rsample and Rstandard are the ¹³C/¹²C ratios in a sample and the standard (Vienna-Pee Dee Belemnite) respectively. Accuracy of the measurements was ± 0.1‰. Carbon isotope discrimination between atmosphere and wood was calculated as (eqn. 2):

$$ \Delta^{13}C = \frac{\delta^{13}C_{air} - \delta^{13}C_{wood}}{1 + \delta^{13}C_{wood} / 1000} \quad (2) $$

where δ¹³Cair is the carbon isotope composition of CO₂ in the atmosphere and δ¹³Cwood is the carbon isotope composition of the

wood powder. Given that δ¹³Cair was -8.07‰ during 2003 and an annual decrease of 0.0281‰ (McCarroll & Loader 2004), δ¹³Cair was estimated at -8.24‰ for 2009. We assumed that the mean value of δ¹³Cair was similar across sites and did only marginally change with the season.

### Basal area increment

The data corresponding to annual circumference (cm) of each individual tree was acquired through the annual growth records from the Centre National de la Propriété Forestière-Institut pour le Développement Forestier. Assuming trunks were circular in section, circumference was used to calculate the radius and eventually basal area for the years 2008 and 2009. BAI (cm² yr⁻¹) for year 2009 was calculated as the difference between the total area corresponding to years 2009 and 2008.

### Statistical analysis

Normality and homoscedasticity of data were checked graphically with residual vs. predicted and normal quantile-to-quantile plots. The data set covering the seven age classes was analysed using linear mixed models fitted with genotype, age and their interaction as fixed effects and site as a random effect. Multiple comparison tests (post-hoc Tukey HSD test) were used to evaluate pairwise differences between age classes within each genotype. Further-

more, each age class was tested for genotype effect and post-hoc Tukey HSD test were used to evaluate pair-wise differences between genotypes within each age class. All tests were performed with R (R Core Team 2012) and R packages “nlme” (Pinheiro et al. 2012) and “multcomp” (Hothorn et al. 2008). All tests and correlations were declared significant at P < 0.05.

## Results

### Carbon and nitrogen percentage

Variance between sites was smaller than residual variance (intercept = 0.731; residuals = 1.84) and model R² resulted at 0.547 for carbon percentage. No genotype-age interaction was detected in the carbon percentage of bulk wood. It differed significantly among genotypes (P < 0.001 – for means, see Tab. 1). A non-significant trend with age was detected due to the slightly lower carbon percentage values at the age of 13 yrs. Nevertheless, carbon percentage did not display any significant trend related to age (Fig. 2). Variance between sites was smaller than residual variance (intercept = 0.009; residuals = 0.071) and model R² resulted at 0.525 for nitrogen percentage. For the nitrogen percentage, no interaction between genotype and age was found. Nitrogen percentage did not differ among genotypes but declined significantly with age (P < 0.001); it dropped from

<figure><img src="image_4.png" /><figcaption>**Fig. 2** - Age-related variation of Carbon percentage in the bulk wood of the year 2009, sampled during winter 2010 in three Populus deltoides × P. nigra genotypes over seven age classes. Each point represents the mean of several sites. Error bars represent ± SE.</figcaption></figure>
**Fig. 3** - Age-related variation of mean nitrogen percentage in the bulk wood of the year 2009, sampled during winter 2010. The curve represents the means of three *Populus deltoides* × *P. nigra* genotypes over seven age classes. Error bars represent ± SE and different letters indicate significant differences between age classes after Tukey HSD test (P < 0.05).

<figure><img src="image_5.png" /></figure>

**Fig. 4** - Age-related variation in carbon isotope discrimination (Δ¹³C) in the 2009 year-ring for three *Populus deltoides* × *P. nigra* genotypes (a) Dorskamp, (b) I-214 and (c) Koster. Each point represents a mean value from several sites. Error bars represent ± SE and different letters indicate significant differences between age classes for each genotype after Tukey HSD test (P < 0.05).

<figure><img src="image_6.png" /></figure>

0.19 down to 0.11% over the tested period (Fig. 3).

### Age and genotype effects for Δ¹³C

Variance between sites was smaller than residual variance (intercept = 0.38; residuals = 0.51) and model R² resulted at 0.99.

Δ¹³C variation was significantly explained by an interaction between genotype and age (P < 0.001 – Tab. 1). A detailed post-hoc analysis revealed that an age effect was detectable in all three genotypes (Fig. 4). There was a significant increase of Δ¹³C by 2‰ from 4 to 9 yrs in Dorskamp and Koster

<table><caption>**Tab. 2** - Carbon isotopic discrimination (± SE) between atmosphere and bulk wood (Δ¹³C) in the year 2009 for three *Populus deltoides* × *P. nigra* genotypes (Dorskamp, I-214 and Koster). Each age class was tested for genotype effect (F-value and P-value) and different letters indicate a significant genotype difference for each age class after Tukey HSD test (P < 0.05).</caption><thead><tr><th>Age class (yrs)</th><th>df</th><th>Dorskamp</th><th>I-214</th><th>Koster</th><th>F-value</th><th>P-value</th></tr></thead><tbody><tr><td>4</td><td>43</td><td>18.9 ± 0.156 <sup>a</sup></td><td>19.3 ± 0.107 <sup>a</sup></td><td>18.1 ± 0.132 <sup>b</sup></td><td>22.3</td><td>&lt;0.001</td></tr><tr><td>7</td><td>47</td><td>20.3 ± 0.179 <sup>a</sup></td><td>20.0 ± 0.172 <sup>a</sup></td><td>18.7 ± 0.179 <sup>b</sup></td><td>18.4</td><td>&lt;0.001</td></tr><tr><td>9</td><td>88</td><td>20.1 ± 0.103 <sup>a</sup></td><td>20.3 ± 0.079 <sup>a</sup></td><td>19.5 ± 0.096 <sup>b</sup></td><td>17.9</td><td>&lt;0.001</td></tr><tr><td>11</td><td>80</td><td>20.9 ± 0.191 <sup>a</sup></td><td>19.9 ± 0.095 <sup>b</sup></td><td>19.8 ± 0.136 <sup>b</sup></td><td>13.8</td><td>&lt;0.001</td></tr><tr><td>13</td><td>24</td><td>20.8 ± 0.095</td><td>20.3 ± 0.175</td><td>20.3 ± 0.150</td><td>3.03</td><td>0.069</td></tr><tr><td>15</td><td>34</td><td>20.6 ± 0.161 <sup>a</sup></td><td>20.1 ± 0.077 <sup>b</sup></td><td>19.8 ± 0.103 <sup>b</sup></td><td>9.26</td><td>&lt;0.001</td></tr><tr><td>18</td><td>39</td><td>20.8 ± 0.092 <sup>a</sup></td><td>19.7 ± 0.151 <sup>b</sup></td><td>19.6 ± 0.443 <sup>b</sup></td><td>19.6</td><td>&lt;0.001</td></tr></tbody></table>

(Fig. 4a, Fig. 4c) and a less visible one in I-214 (Fig. 4b) where it increased from 4 to 7 yrs and remained almost stable afterwards.

Genotype effect within each age group was found significant and was assessed with post-hoc Tukey HSD test (Tab. 2). In the young age classes (4 to 9 yrs), Koster displayed the lowest mean Δ¹³C followed by Dorskamp and I-214 that displayed similar values. At higher ages, Koster and I-214 displayed the lowest and Dorskamp displayed the highest mean Δ¹³C, with the exception of age class of 13 yrs, where no significant difference could be detected.

### Inter annual and genotype correlation between Δ¹³C and BAI

The average BAI of the year 2009 was homogenous among the three genotypes over the tested period (Tab. 1), and therefore the genotypic differences in Δ¹³C were independent from any difference in radial growth rate. The inter annual variation of BAI due to the age effect was positively correlated to Δ¹³C in the three genotypes (Fig. 5)

### Discussion

The present research was aimed to assess the stability of genotype differences in water use efficiency (WUE) with tree age; we compared three cultivars of *Populus deltoides* × *P. nigra* for this trait in plantation *in situ* across France and used a synchronous approach, based on Δ¹³C recorded from the year 2009 of individuals with different ages.

### Genotype and age effect on Δ¹³C and relationship with BAI

Whole wood consists of complex mixtures of molecules like cellulose, hemicellulose and lignin with variable isotopic signatures. Early studies used whole wood for the isotopic analysis on tree rings. However, the isotopic composition of individual wood components differs largely (Wilson & Grinsted 1977). Thus, we suspected that the observed significant genotypic difference in mean Δ¹³C could potentially be due to changes in cellulose vs. lignin ratios with contrasting isotopic signals. Although previous studies have shown that using whole wood is better than inducing extraction error while using cellulose to measure δ¹³C (Guy & Holowachuk 2001, Rasheed et al. 2011), in this study we minimised this effect by using the last annual ring (2009, with same cambial age) for isotope analysis.

Our results showed the existence of an age effect on Δ¹³C, where Δ¹³C increased to a larger extent during first age classes of 4-11 years in two genotypes (Dorskamp and Koster). This positive trend in Δ¹³C with age is contrary to several previous studies reporting age-related decreases in Δ¹³C using different dendrochronological approaches (Bert et al. 1997, Duquesnay et al. 1998, McCarroll & Pawellek 2001, Penuelas et al. 2008). Δ¹³C has been expected to be an estimator of water use efficiency (Farquhar
et al. 1989). Several studies have shown a clear negative correlation between Δ¹³C and A/gs (intrinsic water use efficiency, iWUE) and WUE (whole-plant water use efficiency – Ripullone et al. 2004, Cernusak et al. 2008, Rasheed et al. 2013). Thus, increase in Δ¹³C with age in our study reflects a decrease in iWUE with age. This decrease in iWUE (A/gs) can either be due to decreased CO₂ assimilation rate (A) or increased stomatal conductance (gs – Farquhar & Richards 1984, Condon et al. 2004). Furthermore, Δ¹³C and tree growth are often correlated depending upon the growth environment. This correlation was found to be positive for some species, i.e., *Eucalyptus globulus* Labill (Osorio & Pereira 1994. Pita et al. 2001), *Fagus sylvatica* L. (Dupouey et al. 1993) and *Pinus radiata* (Rowell et al. 2008). On the contrary, some other conifer species displayed a negative correlation between Δ¹³C and growth, i.e., *Larix occidentalis* Nutt. (Zhang et al. 1994), *Pinus pinaster* (Nguyen-Queyrens et al. 1998, Brendel et al. 2002), *Picea mariana* Mill (Johnsen et al. 1999) and *Pinus caribaea* Morelet (Xu et al. 2000). However, no correlation between Δ¹³C and tree growth was found in P. × euramericana in common garden (Monclus et al. 2005) and poplar plantation (Bonhomme et al. 2008). Within each genotype, we found a positive correlation between BAI and Δ¹³C with age, which is in line with previous findings in different *Populus deltoides* × *P. nigra* genotypes (Rasheed et al. 2011). Similar positive correlation between BAI and Δ¹³C has been reported in *Pinus radiata* (Rowell et al. 2008). The positive correlation between Δ¹³C and BAI suggests that the inter-annual variation of Δ¹³C is controlled to a larger extent by stomatal conductance than by photosynthetic capacity (Johnsen et al. 1999, Xu et al. 2000). In poplar, mostly variation in stomatal conductance rather than photosynthetic capacity seems to control carbon gain and growth (Ceulemans et al. 1987, Monclus et al. 2006, Rasheed et al. 2015). Therefore, based on the significant positive correlation between BAI and Δ¹³C across tested genotypes, we may conclude that the observed increase in Δ¹³C with age and inter-annual variation of Δ¹³C was largely controlled by the variation in stomatal conductance rather photosynthetic capacity.

Stability of the genotypic ranking for Δ¹³C

Checking genotype rank stability with age is of central importance for selecting genotypes for higher water use efficiency. Therefore, genotype ranking in *Populus deltoides* × *P. nigra* was tested for Δ¹³C in controlled vs. open field conditions (Monclus et al. 2005) and subsequently, in well irrigated vs. water stress under field conditions (Monclus et al. 2006). In both studies, genotypic ranking remained stable with no correlation found between Δ¹³C and productivity traits. However, these studies were done on young plants. Parallel to

that, many previous studies evidenced an age effect on Δ¹³C and demonstrated that duration and extent of age effect is variable according to many species (Leavitt 2010). In this context, genotype ranking made on young plants were susceptible to change with age. Our results showed that genotype ranking shuffled across first age class (4 years) to seventh age class (18 years), i.e., *l*-214 displayed highest and Koster the lowest Δ¹³C values in the first age class (4 years), whereas *l*-214 was ranking second in the seventh age class (18 years). In spite of rank shuffling with age, genotypic ranking for mean Δ¹³C values matched with that found by Marron et al.

(2005) and Monclus et al. (2005), where Koster had the lowest Δ¹³C and Dorskamp had the highest, and with Rasheed et al. (2011) in Begaar for Dorskamp and *l*-214. Thus, we may conclude that based on a relatively small number of cultivars, a stability of genotype ranking was observed with age in two cultivars, at least during the approach. 20 years from planting to harvest. This conclusion is based on a limited range of cultivars. Unfortunately, extension to a larger number of genotypes was impossible given the lack of suitable even-aged common garden plantation of poplar cultivars at suitable age, not to speak of common gardens with different tree ages.

<figure><img src="image_7.png" /><figcaption>**Fig. 5** - Correlation between carbon isotopic discrimination (Δ¹³C) and basal area increment (BAI) in three *Populus deltoides* × *P. nigra* genotypes (a) Dorskamp: Δ¹³C = 0.0161BAI + 18.9; (b) *l*-214: Δ¹³C = 0.0087 BAI + 19.0; and (c) Koster: Δ¹³C = 0.0138 BAI + 18.0. Each point represents values measured at a given site.</figcaption></figure>
## Conclusion

In this study, Δ¹³C assessed from the year 2009 increased with tree age in the three genotypes, indicating a decrease in water use efficiency with age at whole tree level. Furthermore, inter-annual variation of Δ¹³C was found positively correlated to BAI in all genotypes which shows that Δ¹³C was largely controlled by stomatal conductance rather photosynthetic capacity. Significant genotypic effect was detected for mean Δ¹³C over the tested period. The genotypic ranking of Δ¹³C was: (i) maintained among the three *Populus deltoides* × *P. nigra* genotypes, despite of crossing detected with tree age; (ii) found consistent with the previous ranking for Δ¹³C. Finally, Koster genotype was found highly water use efficient and productive with age among the tested genotypes. However, further studies are required to test other genotypes as well.

## Acknowledgements

The authors are very grateful to Cyril Buré (INRA, UMR EEF) for helping in arranging the field visits and in collecting samples together with the different technicians of CRPF. Christian Hossann and Claude Bréchet (INRA, UMR EEF), for spending time doing all isotope analyses. Finally, we thank WFJ Parsons (CEF) for English editing. We are thankful to two anonymous reviewers for their suggestions to improve the manuscript. The research was supported by the European Union FP7 Project "Novel Tree Breeding Strategies" Project no. FP7 - 211868. F. Rasheed was supported by a grant from the Higher Education Commission of Pakistan.

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**Supplementary Material**

**Tab. S1** - Complete list of 376 tree cores sampled for three genotypes (*Dorskamp*, I-214 and *Koster*) under each age class along with information of each site condition (Water available, WA and Water limiting, WL) and their GPS coordinates.

**Tab. S2** - Coefficients of predictor variable for Carbon, Nitrogen and along with variance explained by sites, which was taken as random factor.

**Tab. S3** - Coefficients of predictor variable for Nitrogen along with variance explained by sites, which was taken as random factor.

**Tab. S4** - Coefficients of predictor variable for Carbon isotope discrimination along with variance explained by sites which was taken as random factor.

Link: Rasheed_2896@suppl001.pdf