Introduction

Forests contribute to the reduction of atmospheric CO2 concentrations and help to mitigate climate change (Grassi et al. 2017). In recent decades, increasing temperatures, water scarcity and the highest frequency of extreme weather events have been observed especially in Mediterranean areas (Giorgi and Lionello 2008; Ripullone et al. 2009a). In this scenario, forest-based mitigation strategies—including afforestation, reforestation and reducing deforestation—are important to reduce atmospheric CO2 and increase C sequestration (Reyer et al. 2009). These practices favor rapid tree growth and carbon sequestration in post-harvest wood products (Harmon and Marks 2002; Kobziar and Stephens 2006; Krankina and Harmon 2006).

Some forestry practices that apparently mitigate global warming such as afforestation activities may actually intensify water use and, therefore, deplete available water reserves (Unkovich et al. 2003; Dias de Oliveira et al. 2005). For example, plantations composed of highly productive species used for bioenergy production generally use much more water than the species naturally occurring in these areas (Jackson et al. 2005). Moreover, certain management practices, such as the use of nitrogenous fertilizers for agriculture and forestry, in some cases may also reduce water-use (Lauteri et al. 1997; Farley et al. 2005; Battipaglia et al. 2017), likely due to interacting effects with drought or nutrient imbalance, leading to interspecific differences in the water-use responses to nitrogen fertilization (Smith and van den Driessche 1992; Ripullone et al. 2004).

Biomass production and intrinsic water-use efficiency (iWUE, as the ratio between carbon assimilation and water transpired) are important parameters that should be considered when choosing tree species for plantations. Although rapid biomass accumulation in fast-growing trees (short rotation forestry) is important in the interests of resource management and environmental sustainability, water consumption (related to the tree water-use and water lost by transpiration) should also be taken into account. Therefore, forest management should preferably focus on species and silvicultural practices that increase C sequestration without reducing groundwater reserves (Unkovich et al. 2003; Dias de Oliveira et al. 2005). Consequently, the choice of trees for use in plantations must factor in both the growth potential and the water use of each candidate species.

Sustainable water management in forested areas (i.e. afforestation, plantation, short rotations) is possible when the carbon to water balance ratio is considered. Under limited water conditions which frequently occur in the Mediterranean, plants partially close their stomata to save water and maintain their leaf water potential within a safety range to prevent cavitation (Ripullone et al. 2009a). Although stomatal control favours water saving, it has a negative effect on plant carbon uptake by down-regulating the CO2 assimilation (Jarvis and Davies 1998). The intrinsic water-use efficiency (iWUE), assessing the ratio between CO2 assimilation and stomatal conductance, is a key parameter in drought-prone areas (Ripullone et al. 2009b; Altieri et al. 2015). Understanding species-specific differences in iWUE may help to elucidate how plantation and afforestation stands respond to drought occurrence.

The carbon isotope composition (δ13C) is a useful proxy to improve understanding of forest responses to climate-changing conditions over time (McCarrol and Loader 2004); it contributes to determining whether a plant species saves water as indirectly related to water-use efficiency (Farquhar et al. 1989a). There is a relationship between iWUE and δ13C because of their independent linkages to the ratio of internal to ambient CO2 concentrations (ci/ca). Studies have reported an increase in iWUE around the globe (Loader et al. 2011; Marchand et al. 2020) and Mediterranean areas (Andreu-Hayles et al. 2011), even if higher iWUE does not always translate into enhanced tree growth (Peñuelas et al. 2011; Silva and Anand 2013; and others). In open field studies, no clear pattern emerged, reporting both active and passive plant response: in the first case ci increases more slowly than ca due to photosynthetic plasticity, resulting in higher iWUE (Duquesnay et al. 1998; Feng 1999; Peñuelas et al. 2008; Guerrieri et al. 2019), while the second case no changes in the caci are highlighted in response to increased atmospheric CO2 concentration (ca), which resulted in no improvement of the iWUE (Marshall and Monserud 1996). Saurer et al. (2014) suggested that site-specific conditions are relevant due to enhanced iWUE in temperate forests of central Europe following a decreasing soil–water availability as a consequence of the ongoing climate change. However, multi-species studies carried out in Mediterranean areas focusing on variations in terms of iWUE growth and plant ecophysiological adjustments are lacking.

We hypothesized that the ongoing climate change should favour iWUE but disadvantage the growth as a consequence of enhancing drought events which negatively affect photosynthetic activity in both conifer and hardwood studied species. To test this idea, we investigated the magnitude of the co-variations in BAI and iWUE across species growing in forestry plantations. We considered contrasting environmental conditions in an afforested stand with conifer species (Pinus halepensis and Cupressus sempervirens) and in a coexisting stand with hardwood species (Quercus robur, Juglans regia, Fraxinus excelsior, and Populus spp), among the most common species used in the past for plantations in Italy. Specifically, we evaluated: (1) the growth in terms of basal area increment (BAI); (2) the intrinsic water-use efficiency (iWUE) as assessed by δ13C in annual tree rings, and (3) the short-term species-specific ecophysiological adjustments, derived from iWUE.

Materials and methods

Study sites

The experiments were conducted at Camisano in northern Italy (Site 1) and at Gallipoli Cognato and Piccole Dolomiti Lucane Regional Parks in southern Italy (Site 2), Table 1.

Table 1 Main characteristics of sites and sampled trees

Site 1 lies in the Padan basin and belongs to a flat area located ~ 30 km east of Milan in northwestern Italy. The climate is classified as mild continental with an average total annual rainfall of 1050 mm, almost equally distributed throughout the year. Maximum precipitation occurs during fall and winter and the average temperature is 10 °C. The natural vegetation of the Padan basin is a mixed hardwood forest consisting of Quercus robur, Populus spp., Carpinus spp., Alnus spp., Salix spp., Fraxinus spp., and other trees indigenous to central Europe. The site is a mixed-species plantation established at the beginning of 1997 and covering 2.8 ha. The above-mentioned species, ecologically and economically important (Colpi et al. 1999), are widely employed in plantations in Italy especially from the 1960s to 1990s of the last century covering more than one million hectares.

The plantation consisted of a main plot (P1) (~ 2.8 ha) with coexisting coetaneous species (Quercus robur, Fraxinus excelsior, and Juglans nigra), and monospecific Populus alba (clone a4) rows (P2), surrounding the main plot. The trees in P1 and P2 were planted in straight rows spaced 5 m apart corresponding to a density of ~ 400 trees per hectare. The crop cycle in P1 and P2 is different: hardwood species in P1 and Populus trees in P2 are managed as arboriculture and short rotation (for biomass energy), respectively. This implies a shorter cultivation cycle for Populus, that showed a different age (9 years old) compared to the other hardwood species (16 years old) sampled in P1. Nevertheless, Populus trees were considered as widely employed species representing a useful reference for biomass production and water use.

Site 2 belongs to a mountain stand located in the South of Italy; the bedrock is an arenaceous stone “Flysch di Gorgoglione” (alternating sandstone, marl, and clay) and the soil texture is mainly sand. The climate is the Mediterranean with a mean total annual rainfall of 687 mm, concentrated in fall and winter, and an average temperature of 12 °C. There is a dry period from June to September during which precipitation is < 100 mm. The stand studied here (~ 150 ha) was planted at the end of the 1960s with trees in rows 3 m apart with an overall stand density of ~ 1200 trees ha−1. The stand is dominated by Pinus halepensis (P) and Cupressus glabra (C); together, they comprise ~ 90% of the vegetation cover and their presence is shared at approximately 50%. In addition, other species such as Phillyrea angustifolia, Pistacia lentiscus, and Ostrya carpinifolia are present. The selected stands belong to a managed area where during 2000s ordinary thinning, with a reduction of 20% of standing biomass, were applied.

Sampling

In spring 2015, 7 and 15 healthy dominant trees representative of each considered species were sampled at the plantation (Site 1) and afforestation (Site 2) stands, respectively. Two wood cores were extracted with an incremental borer at collar level and breast height for each tree at Site 1 and Site 2, respectively.

Samples were air-dried and polished with a scalpel until the lumens of the vessels and tracheids were clearly visible. Tree-ring series were visually cross-dated and ring widths were measured at a 0.01-mm resolution with an incremental measuring table Lega SMIL3 (Corona et al. 1989). Chronologies were checked within a species and site with Cofecha (Holmes 1983).

In our study, we considered even-aged plantations with poplar trees, managed as short rotation forestry that were slightly younger compared to the hardwood tree species sampled at Site 1. Therefore, to evaluate tree productivity in the selected stands by accounting for the age-effect, the raw chronologies were converted into tree basal area increments (BAI) as follows:

$${\text{BAI}}_{t} = \pi r^{2}_{t} - \pi r^{2}_{t - 1}$$

where BAI at year t is the annual ring area; and rt and rt−1 are the stem radii at the end and beginning of the annual increment, respectively. BAI eliminates the age effect associated with stem geometry, reduces low-frequency variability, and obviates the need for detrending (Biondi 1999).

Stable C isotope analysis

For each species, five trees were selected for isotopic analyses. From each dated tree core, single rings were separated with a blade cutter. Each sample was ground in a centrifugal mill (ZM 1000, Retsch, Germany) with a 0.5-mm mesh size to ensure homogeneity. Isotopic analysis was performed on whole wood samples in hardwood species since recent studies have shown that the use of whole-wood isotope values is justified for ecophysiological and dendrochronological studies that analyze the response of trees to environmental changes recorded within the sapwood in a relatively short-term period (Borella et al. 1998; Harlow et al. 2005; Riechelmann et al. 2016). However, in conifer species isotopic analysis was performed on cellulose samples, to avoid biases on isotope value due to contamination by other wood extractives (Borella et al. 1998; D’Alessandro et al. 2004). For the extraction of cellulose a two-step digestion process was followed (Boettger et al. 2007; Battipaglia et al. 2008). The method is based on a double step digestion: first step was performed for the extraction of resin, fatty acids, ethereal oils and hemicellulose with a solution of 5% NaOH for 2 h at 60 °C—this operation was repeated twice. In the second step, lignin was extracted with a 7% NaClO2 solution for a minimum of 36 h at 60 °C. Because the solution is only reactive for about 10 h, it was changed daily and refilled as necessary. This step was repeated until the sample was “white”, which is a characteristic that can be determined by experience or by comparison with commercial cellulose (Boettger et al. 2007). Finally, samples were washed three to four times with boiling distilled water (until pH = 7 ± 1) and dried overnight at 50 °C.

0.06 mg wood and alpha-cellulose material were weighed in tin capsules, for hardwood and conifer species, respectively. Stable C isotope composition was measured at the IRMS-SUN Laboratory (Caserta, Italy) by a combustion in an elemental analyzer (Carlo Erba, 1110 Milano, Italy) connected via a CONFLO II interface (Thermo Finnigan, Breen, Germany) to an isotope ratio mass-spectrometer (Delta V Advantage, Thermo Electron Corporation, Bremen Germany) operating in the continuous flow mode. Isotopic compositions are expressed in delta notation (%) relative to an accepted reference standard: Vienna PeeDee belemnite for carbon isotope values. The standard deviation for the repeated analysis of an internal standard (commercial cellulose) was < 0.01‰.

Calculation of iWUE from C isotope ratios

Carbon isotope composition in tree rings (δ13C) reflects the variations in the CO2 concentration ratio between the leaf intercellular spaces and the atmosphere (ci/ca). These are related to changes in carbon assimilation (A) or stomatal conductance (gs). A simplified version of the Farquhar equation (Farquhar et al. 1989b) determines the δ13C in plant material (δ13Cp) as follows:

$$\delta^{13} C_{{\text{p}}} = \delta^{13} C_{{\text{a}}} {-}a{-}\left( {b - a} \right)\frac{{c_{{\text{i}}} }}{{c_{{\text{a}}} }}$$
(1)

where δ13Ca and ca indicate the isotopic signature of atmospheric CO2, a is the fractionation against 13CO2 during diffusion through stomata (4.4%), and b is the fractionation during carboxylation (27%) by the CO2-fixing enzyme rubisco. In the iWUE calculation, the mesophyll conductance of CO2 (Seibt et al. 2008) and post-photosynthetic processes that may potentially affect tree-ring δ13C (Gessler et al. 2014; Frank et al. 2015) were not considered. Since ci/ca and δ13C are reciprocally linked, the latter is indicative of changes in the iWUE, which is the ratio between A and the stomatal conductance to water vapor (gH2O) according to Ehleringer et al. (1993):

$${\text{WUE}}_{i}= \frac{A}{{g}_{\text{H}2\text{O}}} = \frac{\left({c}_{\text{a}}- {c}_{\text{i}}\right)}{1.6}$$
(2)

From Eq. (1), ci is calculated as follows:

$${c}_{\text{i}}={c}_{\text{a}} \frac{{\delta }^{13}{C}_{\text{a}} - {\delta }^{13}{C}_{\text{p}} -a}{b -a}$$
(3)

Therefore the Eq. (2) can be solved as follows:

$${\text{WUE}}_{i}= \frac{A}{{g}_{\text{s}}}= \frac{{c}_{\text{a}}-{c}_{\text{i}}}{1.6}=\frac{{c}_{\text{a}}}{1.6} \times \left(\frac{b-{\delta }^{13}{C}_{a}+ {\delta }^{13}{C}_{p}}{b-a}\right)$$
(4)

where δ13Ca and ca values were obtained from Mauna Loa records (Keeling et al 2001); 1.6 is the molar diffusivity ratio of CO2–H2O (i.e., gCO2 = gH2O/1.6); the values a and b are known, ci is calculated from Eq. (3), δ13Cp is the carbon isotope composition measured in tree rings.

Statistical analyses

The six tree species sampled were subdivided into the hardwood species Juglans nigra, Quercus robur, Populus spp., and Fraxinus excelsior (Site 1) and the conifers Pinus halepensis and Cupressus glabra (Site 2). BAI data were log-transformed before analysis to meet the normality assumptions. The LMM was fitted to assess the effect of age, species, iWUE and their interactions (fixed factors) on BAI, where individual trees were considered as random effects to account for repeated measures within a site. Following Zuur et al. (2009), the most parsimonious models were selected starting with a saturated model where the fixed component contained all explanatory variables and their possible interactions, using the ‘nlme’ package (Pinheiro et al. 2020) from R environment v.4.0.0 (R Core Team 2020). Fixed terms were centered and scaled to improve parameter estimates and allow direct comparisons of the regression coefficients. We then optimized the random-effect structure of the model, testing whether including extra random-effect terms (i.e., random slopes) for tree ID improved the fit of the model; different random structures were compared through a Likelihood Ratio Test (LRT, which approximately follows a chi‐square distribution; Zuur et al. 2009). When comparing saturated models that varied in their random structure but not fixed effects, the models were fit using restricted maximum likelihood (REML) to avoid biased estimators for the variance terms. The fixed-effect structure was optimized by fitting the model with Maximum Likelihood (ML), rather than REML, to prevent biased fixed-effect parameter estimates. We conducted AICc values (Akaike Information Criterion corrected for sample size) based on multi‐model inference using the “MuMIndredge function (Barton and Barton 2020) to run a complete set of models with all possible combinations of the fixed effects, with ∆AICc < 2 interpreted as substantial support that the model belongs to the set of ten best models, ∆AICc of 4–7 corresponding to less support and ∆AICc > 10 treated as providing no support that the model belongs to the best (Burnham and Anderson 2002). Finally, models were refitted with REML to estimate model parameters. Marginal and conditional R2 scores (Nakagawa and Schielzeth 2013) were calculated to examine the variation explained by models using the “r.squaredGLMM” function in the “MuMIn” package. The residual diagnosis was performed to check the validity of the model assumptions (normality and homoscedasticity of residuals). Subsequently, the lstrends function from the ‘lsmeans’ R package (Lenth 2016) was used to estimate and compare, via Tukey post‐hoc test, species-specific slopes of fitted lines.

For each species, we further evaluated the temporal pattern of iWUE components (i.e. ci, ci/ca, caci), by inspecting the slope of the regression line via LMMs where cambial age was included as fixed-term and sampled trees as random. The models were then parametrically bootstrapped 1000 times using the bootMer function in package ‘lme4’ (Bates et al 2015) from which the predicted median and 95% confidence interval of the beta estimates were calculated.

Results

Basal area increment and intrinsic water-use efficiency

In general, a substantial range of variation of iWUE and BAI was observed (Fig. 1). For all hardwood species, except Populus, different BAI was measured for similar iWUE distribution ranges. Conifers showed contrasting differences between the recorded variables, i.e., Cupressus showed greater water-use efficiency, but was less productive in terms of tree growth than Pinus.

Fig. 1
figure 1

Temporal variation in intrinsic water use efficiency (iWUE, upper panels) and basal area increment (BAI, lower panels) for plantation (a, c) and afforestation stands (b, d) over the studied period. Points with different colors represent means of different species in each year; bars are standard errors. Insets represents boxplots of species-specific iWUE and BAI. Each box represents the 75th–25th percentiles, the bold line shows the median, upper and lower marks are the largest to smallest observation values which are less than or equal to the upper and lower quartiles plus 1.5 times the length of the interquartile range. Circles outside the lower–upper mark range represent outliers. Different letters indicate significant differences among species (P ≤ 0.05) Tukey’s pairwise post-hoc comparisons

The hardwood species all had similar annual iWUE during 1996–2010, except for Populus (Fig. 1a). The iWUE for the conifers showed higher interannual variability compared to the considered hardwood species (coefficient of variation was 12.5% and 10.4% for conifers and hardwood, respectively). BAI and iWUE variations at Site 2 were observed in correspondence to the thinning operations in both Cupressus and Pinus stands, which likely occurred in 2003 and 2009 (Fig. 1). The iWUE for Pinus was significantly lower than Cupressus (Fig. 1b); overall, Cupressus exhibited the lowest BAI (Fig. 1c) whereas Populus the highest (~ 2500 mm2), which was also the youngest sampled tree species at Site 1 (Fig. 1c).

The role of iWUE in determining BAI

Species characterized by different strategies for achieving high/low BAI in relation to high/low values of iWUE were depicted (Fig. 2a). In particular, among hardwood species, Populus showed the highest iWUE value while Fraxinus displayed the lowest value. Between conifer species, Cupressus showed the lowest and Pinus the highest iWUE value per BAI. Figure 2b describes the slopes of the species of BAI on iWUE, whereas the model structures, covariates with model coefficients, standard errors, and significance levels are summarized in the Supplementary Table S1. In particular, the selected model showed that 71% of the total variance was attributable to the fixed effects whereas less than 1% of the variance was attributable to variation between trees. While no evidence for a main effect of iWUE on BAI was found, differences among species (Supplementary Table S2) are evident where the slopes of the relations with BAI of Populus and Pinus are significantly higher and lower respectively compared to the main effect (i.e. Cupressus), while an opposite slope was observed for Quercus (Fig. 2b). As expected, tree age had a negative influence on BAI.

Fig. 2
figure 2

The relationship between BAI and iWUE is represented in both panels. In a circles and bars represent mean values and standard deviations for each investigated tree species; the dashed lines shows 1:1 relationship. b Shows comparison via Tukey post‐hoc test of species-specific slopes of the relationship BAIiWUE from fitted LMM. Different letters indicate significant differences among species at P ≤ 0.05

Variations in the iWUE components

In general increasing ci and ci/ca trends were observed with differential iWUE trends, as assessed by caci temporal variations (Table 2). In particular, the following main results for caci were observed: a significant increasing trend for Cupressus and a significant decreasing trend for Fraxinus, Juglans, and Quercus species; relatively decreasing, and non-significant trends for Pinus and Populus species. Non-significant variations for ci/ca were recorded for Cupressus and Pinus, respectively, whereas positive significant trends were recorded for Fraxinus, Juglans, Populus, and Quercus species.

Table 2 Observed temporal patterns in components of intrinsic water-use efficiency

Overall ci/ca ratios varied among species showing lower values in conifers than hardwood species (Fig. 3a); a consistent ci adjustment with respect to the increasing ca was evident in all considered species, although a short-term period was considered (Fig. 3b).

Fig. 3
figure 3

a Boxplots of ratio between intercellular to ambient carbon dioxide concentration for considered species. Each box represents the 75th–25th percentiles, the bold line shows the median, upper and lower marks are the largest to smallest observation values which are less than or equal to the upper and lower quartiles plus 1.5 times the length of the interquartile range. Circles outside the lower–upper mark range represent outliers. b Temporal species-specific relationships between ambient (ca, x axis) and intercellular (ci, y axis) carbon dioxide concentration; lines draw each predicted LMMs as a function of ca and cambial age as covariates and tree ID set as random; slope coefficients and their standard error of coefficients (in bracket) are reported nearby fitted lines. * and ** indicate statistical significance for P < 0.05 and P < 0.01, respectively

Discussion

In this study, we analyzed the iWUE and BAI in a range of tree species, mostly used in Italy in former forestry plantation practices to provide functional-based indications on tree species selection.

The observed strategies for achieving (relatively) high/low iWUE (Fig. 2a) are closely related to differences in physiological mechanisms among species. Indeed, different iWUE levels may be linked to a greater overall CO2 assimilation capacity of some species or a better stomatal control in other species. Populus was distinct from the other species due to its iWUE comparatively low coupled to a high growth rate, whilst Juglans and Fraxinus appeared to have reached a better carbon–water balance, although showing a weak association between considered variables (Fig. 2b). On the contrary, the opposite associations between BAI and iWUE reported for Quercus may be explained by a greater stomatal control compared to the other coexisting species i.e. avoiding water loss by stomatal closure and, consequently, enhancing iWUE to the detriment of growth. Similar findings have also been reported in previous studies in both seedlings, under controlled environmental conditions (Picon et al. 1996), and adult trees, growing in natural forests subjected to dieback phenomena not far from experimental Site 1 (Colangelo et al. 2018).

One of our objectives was to understand the magnitude of the co-variations in BAI and iWUE across species growing in a forestry plantation. When considering growth (in terms of BAI) as explained by plant ecophysiological trait (iWUE), age and species, our results did not support evidence for a general trade-off between annual growth and iWUE. A flat or weak relationship was observed for Juglans, Fraxinus, and Pinus species; positive relationships for Populus and Cupressus while a negative relationship was found for Quercus (Fig. 2b).

This general uncoupling between iWUE and BAI has been widely observed in literature. Indeed, several studies report that the enhanced iWUE observed in the last century (Andreu-Hayles et al. 2011; Leonardi et al. 2012; Frank et al. 2015; Marchand et al. 2020) did not translate into an increase in tree growth (Peñuelas et al. 2011; Silva and Anand 2013; Lévesque et al. 2014). Moreover, site-specific studies are often carried out in open-fields along a latitudinal gradient to appreciate species-specific adaptations to changing climatic conditions by evaluating plant physiological traits adjustments (Guerrieri et al. 2019; Fu et al. 2020). In general, contrasting relationships between BAI and iWUE, e.g. a negative relationship for conifer whereas positive relationships for hardwood species (Scots pine and European beech in González de Andrès et al. 2018) were evident; no common patterns were observed when intra-specific comparisons were carried out (González-Muñoz et al. 2015) and very few studies have been carried out on plantations, i.e. clones of Populus (Rasheed et al. 2019). A recent review (Walker et al. 2020) suggested a major increase in iWUE in water-limited regions where long-term transpiration is primarily precipitation driven (i.e. plants use the available water).

Most species considered in our study did not report substantial time-related enhanced BAI and iWUE, showing rather flat or even negative trends (Table 2). This is in contrast with the latest literature (Peñuelas et al 2008; Battipaglia et al. 2013; Guerrieri et al. 2019; Walker et al. 2020) where an increase in iWUE is reported. No evidence of increased carbon uptake per unit water loss has been recognized, in agreement with literature studies (Huang et al. 2007; Peñuelas et al. 2008, 2011; Andreu-Hayles et al. 2011; Franks et al. 2013). This could reflect a water-saving strategy in which the stomata are closed, thereby enhancing iWUE (Battipaglia et al. 2013) or even a climate-related effect, indeed, in some cases, the trade-off carbon uptake per water loss is strongly dependent on the occurrence across the years of favorable/unfavorable climatic conditions (Granda et al. 2014).

Short-term species-specific adjustments

Even short-term variations in the ratio and difference of intercellular to ambient CO2 concentrations can indicate species-specific acclimations to current environmental conditions. According to Saurer et al. (2004), we could observe three scenarios with respect to the possible responses of ci to increasing ca: (a) ci/ca remains constant when the tree actively controls ci; (b) the increments in ci and ca are the same and ci passively follows ca and their relative differences do not change; (c) ci transiently rises faster than ca so that ci/ca increases and caci decreases. The control of ci (the capacity of the plant to reduce the impact of changes in ca, or ci homeostasis) decreases from scenario (1) to (2) and from scenario (a) to (c )above.

Species-specific acclimations to recent increases in atmospheric CO2 concentrations were evaluated from temporal variations in the ratio and the differences between ci and ca (Fig. 3, Table 2). In general, the species considered in our study showed quite a similar behavior of ci at the increasing ca registered in the last few years, with lower ci/ca ratios observed in conifers compared to hardwood trees (Fig. 3a). In agreement to published studies (Guerrieri et al. 2019) this evidence could underline species-specific differences in mesophyll conductance (Flexas et al 2008) and leaf photosynthetic components (Bahar et al. 2018). However, this increasing trend (Fig. 3b) did not directly translate in a common response of selected species when considering time-related trends, accounting for cambial age and within tree variation (Table 2). Indeed, all species (except for Cupressus) showed flat iWUE trends, possibly linked to variations in either A or gs.

Our results at first confirm that not all tree species save water equally in either conifer and hardwood species (Leonardi et al. 2012; Saurer et al. 2014; Frank et al. 2015); also we must recognize that our study, although considering sites with quite similar climate variations (Figs. S1 and S2), considers artificial plantation areas of introduced tree species where site-specific conditions, in particular water table depths, are quite different. Indeed at Site 1, a greater available soil water reservoir for trees is vital to mitigate the occurrence of drought stress events; conversely, at Site 2, conifer plantations are subjected to high temperatures and frequent drought episodes that would lower soil water potential, which can induce stomatal closure (McDowell et al. 2008) and reduce photosynthetic carbon uptake (Wang et al. 2017). At elevated temperatures, plants tend to close their stomata to prevent excessive water loss, increasing iWUE, as observed, for example, in pine forests on the Iberian Peninsula (Andreu-Hayles et al. 2011). Moreover, high temperature and extreme heat events can worsen drought stresses (Teskey et al. 2015) and exacerbate the effects of increasing CO2 concentrations on iWUE (Norby and Zak 2011; Tognetti et al. 2014; Kwak et al. 2016).

In addition, the observed patterns could be partially related to differences in carbon allocation (e.g., increasing leaf area index or developing a deeper root system) among the species. Indeed, except for Populus, the hardwood species at Site 1 did not show enhanced growth in terms of basal area (Fig. 1c). Therefore, there is no evidence here to support an increase in A; a reduction in gs is most likely responsible for the observed decreasing caci patterns. In our data set, we observed constant ci/ca trends correlated with an increase in caci and iWUE for conifers while for broadleaves, flat or slightly increasing ci/ca trends associated to a flat or slightly decreasing caci and iWUE trends (Table 2). Our results suggest that conifers and Cupressus in particular, has the highest plasticity in terms of regulating stomata in response to rising atmospheric CO2 concentrations; as the increase in iWUE was associated with constant ci/ca. In these specific cases, our observations support the hypothesis that there is an active mechanism maintaining a constant ci/ca ratio associated with increased iWUE, as corroborated by previous studies (Peñuelas and Azcon-Bieto 1999; Feng 1999; Saurer et al. 2004; Peñuelas et al. 2008, 2011).

Conclusions

The following main conclusions can be drawn from our study:

  1. 1.

    BAI and iWUE showed a high species-specific degree of variation depicting less and more efficient species within conifers and hardwood trees; site-specific climate conditions and water availability differentially influenced iWUE.

  2. 2.

    All the considered species showed similar short-term ecophysiological adjustments with respect to the ongoing rise in CO2 concentrations; in a few cases, the hypothesis of an active plant mechanism, maintaining a constant ratio between intercellular and ambient CO2 concentrations, was observed, i.e. Cupressus, the less productive and more water saving within the considered species.

  3. 3.

    Juglans, Fraxinus and Pinus seem to show the best performance in terms of carbon and water balance, providing functional-based indications on tree species selection for forestry plantations.

However, further studies incorporating a greater number of conifers and hardwood species are necessary; in this sense, this study can give first useful attempts.

Author contribution statement

AMSF and FR supported and supervised the research, FR designed the research, MC and AL conducted fieldwork, TG and MC conducted lab work supervised by SA and GB; AR performed statistical analyses. TG wrote the paper with inputs from GB, MB and FR and all the authors contributed to the preparation of the final manuscript.