Skip to main content
NCBI home page
Wiley Open Access Collection logoLink to Wiley Open Access Collection
. 2022 Aug 1;236(2):547–560. doi: 10.1111/nph.18384

Impact of warmer and drier conditions on tree photosynthetic properties and the role of species interactions

Margaux Didion‐Gency 1,✉, Arthur Gessler 1,2, Nina Buchmann 3, Jonas Gisler 1, Marcus Schaub 1, Charlotte Grossiord 4,5
PMCID: PMC9804646  PMID: 35842790

Summary

  • Increased temperature and prolonged soil moisture reduction have distinct impacts on tree photosynthetic properties. Yet, our knowledge of their combined effect is limited. Moreover, how species interactions alter photosynthetic responses to warming and drought remains unclear.

  • Using mesocosms, we studied how photosynthetic properties of European beech and downy oak were impacted by multi‐year warming and soil moisture reduction alone or combined, and how species interactions (intra‐ vs inter‐specific interactions) modulated these effects.

  • Warming of +5°C enhanced photosynthetic properties in oak but not beech, while moisture reduction decreased them in both species. Combined warming and moisture reduction reduced photosynthetic properties for both species, but no exacerbated effects were observed. Oak was less impacted by combined warming and limited moisture when interacting with beech than in intra‐specific stands. For beech, species interactions had no impact on the photosynthetic responses to warming and moisture reduction, alone or combined.

  • Warming had either no or beneficial effects on the photosynthetic properties, while moisture reduction and their combined effects strongly reduced photosynthetic responses. However, inter‐specific interactions mitigated the adverse impacts of combined warming and drought in oak, thereby highlighting the need to deepen our understanding of the role of species interactions under climate change.

Keywords: downy oak, drought, European beech, J max , photosynthetic properties, species interaction, Vcmax , warming

Introduction

Global warming and more frequent and extreme droughts are critical environmental drivers for forest dynamics because of their impacts on atmospheric carbon dioxide (CO2) acquisition through photosynthesis and tree carbon dynamics (Ciais et al., 2005; Rödenbeck et al., 2020). However, although nearly all studies caution that higher temperatures and droughts are increasingly co‐occurring (Overpeck, 2013; Sun et al., 2019), little is known about their combined impacts on tree photosynthetic properties.

Exposure to elevated air temperature but sufficient soil moisture supply should increase leaf‐level photosynthetic properties in the long term because of enhanced photochemical reactions, as long as temperatures do not exceed the photosynthesis optimal temperature (Dreyer et al., 2001; Way et al., 2015; Dusenge et al., 2019). Hence, warming can translate into higher light‐saturated assimilation (A sat) (e.g. Prieto et al., 2009) and more efficient leaf‐level photochemistry. For instance, warming has been associated with higher maximum rate of carboxylation by Rubisco (Vcmax) and maximum photosynthetic electron transport rate (J max), especially when plants are limited by cold temperatures (e.g. Way & Oren, 2010). However, once the optimal temperature threshold of photosynthesis is exceeded, exposure to heat stress could cause the separation of the light‐harvesting complexes from the photosystem II (PSII) reaction center or the denaturation of proteins (Gounaris et al., 1984; Yamane et al., 1997). The consequences are reduced A sat, Vcmax, and J max with high temperatures (Medlyn et al., 2002; Dai et al., 2021; Dusenge et al., 2021), a reduction of the maximum photochemical efficiency (F v/F m) and decreasing chlorophyll (Chl) concentrations. Variation in these responses largely depends on the species' temperature range. Húdoková et al. (2022) observed that heat waves of +5°C above daily average during the summer reduce A sat, PSII, and increase the degradation of Chl in temperate European beech trees (Fagus sylvatica L.), while sessile oak, a Mediterranean tree species growing in warmer and drier environments, showed no effect. Thus, species adapted to higher temperature may better resist future conditions, while more sensitive ones may be seriously threatened ecologically.

Low soil moisture can impact the leaf‐level photosynthesis through stomatal regulation and nonstomatal processes (Flexas & Medrano, 2002). Reduced moisture decreases stomatal conductance, and thus leaf photosynthetic CO2 assimilation due to a reduction of CO2 diffusion and thus lower intracellular CO2 concentration in the leaf (C i) (Gallé & Feller, 2007; Zhou et al., 2014), leading to a possible photo‐damage to PSII (Powles, 1984; Epron & Dreyer, 1993). Independently of stomatal closure, biochemical processes will be affected during prolonged soil moisture reduction, thereby limiting leaf‐level photosynthesis properties via a downregulation of Rubisco activity and content (Parry, 2002). Hence, impacts of low soil moisture could include a reduction of A sat, Vcmax, J max, and F v/F m (Zhou et al., 2014; Santos et al., 2018). For instance, Arend et al. (2013, 2016) showed reduced A sat and impaired PSII photochemistry in drought‐exposed beech and downy oak trees (Quercus pubescens Willd.), including stronger impacts in beech because of its higher vulnerability to low moisture. Indeed, beech is considered rather isohydric compared to oak as this species will close its stomates at less negative leaf water potentials (Klein, 2014) and is generally assumed to be negatively affected by drought (Gessler et al., 2006).

How species respond to the combined effects of rising temperature and low soil moisture depends on the species tolerance, the range of environmental conditions, and how extreme temperature and precipitation changes are. Some studies have reported strong exacerbated effects of combined warming and high soil moisture stress (Contran et al., 2013; Arend et al., 2016). However, combined effects are not always occurring as plants can acclimate leaf‐level photosynthetic properties in response to the environment (e.g. Arend et al., 2011). For example, Grossiord et al. (2017) observed that piñon pine and juniper trees growing in semi‐arid environments where drought is a recurrent stress have stronger leaf‐level responses to soil moisture than to warming with no exacerbation of their combined effects. Moreover, prolonged exposure to warming and low soil water availability can lead to whole‐plant structural acclimation (i.e. shift in biomass allocation), allowing plants to maintain leaf‐level gas exchange under more stressful conditions (Thomas, 2000; Bréda et al., 2006; Schönbeck et al., 2022). Thus, drought and warming can have distinct or similar effects on the photosynthetic properties depending on species‐specific responses to temperature and soil moisture, making projections about their combined effect a big challenge for plant ecologists and land managers (Mittler, 2006; Rennenberg et al., 2006).

In addition to the direct impacts of chronic warming and reduced soil water on individual trees, plant performance in natural ecosystems is driven by the dynamics of the whole forest, including the interactions between trees (Grossiord, 2019). Depending on the species identity, climate, and site conditions, these interactions can have either positive, negative, or no feffects on plant functioning (Hooper et al., 2005; Grossiord et al., 2014a,b,c; Jucker et al., 2016). More specifically, interactions between tree species with complementary structural (e.g. different rooting depths and canopy heights) and functional traits (e.g. phenology, hydraulic traits) have often been associated with mitigating effects during extreme events like droughts (e.g. Grossiord et al., 2014a,b,c; Anderegg et al., 2018; Grossiord, 2019). The potential drivers of such positive effects are associated with niche complementarity and the local environmental conditions created by tree neighbors (Paquette & Messier, 2011; Liang et al., 2015). Local neighbors can increase canopy stratification, and thus decrease the risk of light‐damage (Mensah et al., 2018; Kothari et al., 2021), potentially leading to higher A sat during warmer and drier climate. Similarly, having a more diverse litter input (i.e. litter provided by numerous species) can increase soil nutrient content (e.g. Zak et al., 2003). Higher soil fertility can enhance tree‐level photosynthetic properties (Gessler et al., 2017; Gillespie et al., 2020). However, to our knowledge, no study has experimentally tested how tree species interactions mitigate leaf‐level photosynthetic responses to warming and reduced soil moisture acting alone or combined over multiple years.

We, thus, aimed to understand how the interactions of two co‐existing, broadly distributed but contrasting tree species, i.e. European beech and downy oak, influence their leaf‐level photosynthetic responses to air warming and reduced soil moisture. We exposed young trees in intra‐ or inter‐specific interactions to air warming and reduced soil moisture alone or combined. The tree species were selected because of their distinct functional strategies to deal with warmer and drier climate. European beech is a temperate species growing in moist environments, with mean annual temperatures varying between 2 and 14°C (Durrant et al., 2016), which tolerates shady conditions. Downy oak is growing in direct light in warmer sub‐Mediterranean regions (mean annual air temperatures varying between 5 to 17°C; Pasta et al., 2016). Previous work showed that the interaction between beech and oak can lead to belowground water source partitioning (Zapater et al., 2011; Grossiord et al., 2014a,b,c) and higher productivity (Jourdan et al., 2020) at the tree‐level, suggesting a mitigating effect of their interaction. However, when environmental conditions become too stressful, an adverse effect of the interaction between these species on leaf‐level gas exchange has also been observed (e.g. Didion‐Gency et al., 2021).

Our objectives were to (1) determine how warming and reduced soil moisture acting alone or combined influenced the leaf‐level photosynthetic properties (i.e. A sat, J max, Vcmax, F v/F m and Chl) in beech and oak, and (2) assess how the interactions among these two species impact their leaf‐level photosynthetic properties to warming and soil moisture reduction. If grown in intra‐specific composition, we expect (1) oak to have higher leaf‐level photosynthetic properties with warming compared to ambient conditions while beech will have lower leaf‐level photosynthetic properties because of its stronger vulnerability to high temperatures. Reduction in soil moisture will decrease the photosynthetic properties of both species but with larger reductions expected in beech. Combined warming and low soil moisture will exacerbate photosynthetic responses observed under reduced soil moisture acting alone because of enhanced water stress. If grown in inter‐specific interactions, we expect (2) warming to enhance the photosynthetic properties of oak and mitigate the reduction in beech compared to those under intra‐specific interactions. Tree responses to soil moisture reduction in inter‐specific interactions (i.e. acting alone or combined with warming) will be less impacted than in intra‐specific interactions.

Materials and Methods

Experimental design

The study was conducted at the Model Ecosystem Facility of the Swiss Federal Research Institute for Forest, Snow and Landscape WSL, Birmensdorf, Switzerland (47°21′48″N, 8°27′23″E, 545 m above sea level (asl)). The experimental set‐up consisted of 16 hexagonal glass‐walled open‐top chambers (OTCs) of 3 m height and 6 m2 area (Fig. 1; Schönbeck et al. (2021), Grossiord et al. (2022)). The OTCs were covered by mobile glass roofs kept closed during the whole experiment to exclude natural precipitation. The glass walls and roofs reduced photosynthetic active radiation (PAR) inside the OTCs by about 50% compared to the outside. Each chamber has a belowground volume of 9 m3 divided with concrete walls into two semicircular lysimeters (1.5 m deep, 2.5 m2). Each of the two lysimeters is separated into four compartments with plexiglass walls, leading to a total of eight soil compartments per OTC, of which 72 were used in this study. In October 2018, the lysimeters were filled with a 1 m deep layer of gravel, allowing fast drainage, and covered with a fleece layer to avoid root proliferation past the soil layer. On top of the fleece layer, each compartment was filled with 50 cm of an artificial forest soil provided by the company Ökohum (Herbertingen, Germany; pH 6.3, 40% quartz sand, 20% white peat, 20% expanded shale, 16% pumice stone, and 4% clay). Soil fertilization was conducted every year in spring using granules (Unikorn I; Hauert, Grossaffoltern, Switzerland) with an amount of 30 g per compartment (20% potash, 14% nitrogen, 12% sulfur, 4% phosphate, 3% magnesium). Air temperature and humidity at 50 cm and 2 m above the ground were monitored inside each OTC every 10 s, and an average value of 10 min was stored (Atmos 14; Meter Group Inc., Pullman, WA, USA). Soil temperature and moisture were monitored at 25 cm depth every minute, and an average value of 10 min was stored (5TM; Decagon Devices, Pullman, WA, USA). To obtain homogeneous irrigation, six sprinklers (10 cm high) per lysimeter were equally distributed among the four compartments. Compartments were irrigated automatically every 2 d from April to November, and manually twice a month from December to March to avoid frost damage to the pipes. Leaf litter was left in each compartment during the experiment.

Fig. 1.

Fig. 1

Open in a new tab

(a) Aerial pictures of the 16 open‐top chambers with the four treatments: control (blue), soil moisture reduction (gray), warming (orange), and warming + soil moisture reduction (purple) (n = 4 chambers per treatment). (b) Picture showing the side of the open‐top chambers during the measurement campaign of September 2021. (c) Aerial picture from a control chamber including a central fan and eight compartments with different species interactions between beech and oak trees. (d) Aerial picture from a warming + soil moisture reduction chamber including a central heating system and eight compartments with different species interactions between beech and oak trees.

In October 2018, 288 trees of 3‐yr‐old seedlings of European beech (64 ± 12 cm height) and Mediterranean downy oak (63 ± 11 cm height) were planted in two species interaction treatments: intra‐specific interactions (four trees of the same species per compartment, n = 4 trees) and inter‐specific interactions (two trees from each species per compartment, n = 4 trees). In June 2019, after the first campaign of measurements (see detailed list later), a fully crossed combination of two air temperature and soil moisture regimes was started. This resulted in four climatic treatments: a control with ambient air temperature and irrigation at field capacity (C), a warming treatment with an increase of air temperature of around 5°C (i.e. +4.98°C ± 0.6°C) above ambient temperature of the control (W), a soil moisture reduction treatment with a reduction of soil moisture of around 50% (i.e. −46.23% ± 9.9%) relative to the control (MR), and a combined warming + soil moisture reduction treatment where combined warming and reduced soil moisture were applied simultaneously (WMR) (i.e. +4.81°C ± 0.6°C and −47.4% ± 10.3%; Fig. 2). To maintain −50% soil moisture in the MR and WMR treatments, irrigation levels were adjusted throughout the year in each treatment. Each combination of climatic treatment (n = 4), species (n = 2) and species interactions (n = 2) was repeated six times. One tree per species was randomly selected for the measurements in each compartment per OTC, leading to 96 trees in total (n = 6 trees per species, climatic treatment, and species interactions). While the objectives of this study was not to assess and predict plant responses under real‐world conditions but to better understand the physiological mechanisms under prolonged heat and drought stress, an increase in air temperature of about 5°C and a decrease of 50% in irrigation was selected at our facility to match values observed during extreme events in the study region (e.g. the hot droughts of 2003 and 2018; Rebetez et al. (2006); Schuldt et al. (2020)).

Fig. 2.

Fig. 2

Open in a new tab

Air temperature, vapor pressure deficit (VPD), and soil water content (SWC) under control (blue), soil moisture reduction (gray), warming (orange), and warming + soil moisture reduction (purple) measured in the open‐top chambers. Solid lines show the daily averages (n = 4 chambers per treatment), dashed vertical lines indicate the measurements' campaigns, black filled dots stand for the averages during the campaigns (i.e. average of all 16 open‐top chambers), color‐filled dots show the yearly averages (mean ± SE), and open color dots show the daily maximum and minimum over the entire year in each climatic treatment.

Five physiological traits related to the photosynthetic properties were measured on all selected trees three time during the growing season (i.e. early, middle and late growing season) for 3 yr (i.e. from 2019 to 2021).

Physiological measurements

Foliar gas exchange

Measurements of the light‐saturated assimilation (A sat), maximum carboxylation rate (Vcmax), and the maximum photosynthetic electron transport rate (J max) were carried out in the form of CO2 response curves (A/C i curves). Measurements were done using a Li‐Cor 6800 infrared gas analyzer system (Li‐Cor, Lincoln, NE, USA), except in September 2020, where a Li‐Cor 6400 infrared gas analyzer system was used. One mature and fully sun‐exposed leaf from the top third of the canopy was selected from each tree. The measurements were carried out between 09:00 and 16:00 h when the trees were the most active, excluding periods of midday stomatal closure if they occurred (mostly between 00:00 and 14:00 h in the middle of the growing season). The measurements were conducted with a reference CO2 concentration in sequence steps of 400, 300, 200, 100, 50, 0, 400, 400, 600, 800, 1000, 1200, 1500, 2000 ppm, with the following settings: 1500 μmol m−2 s−1 light‐saturating photosynthetic photon flux density, block temperature approximately. Matching mean daytime (between 09:00 and 16:00 h) ambient air temperature during each campaign (i.e. 20°C: early 2019, 2020, middle 2021, late 2019, 2020, 2021; 25°C: early 2021, middle 2019, 2020) with an increase of +5°C in W and WMR compared to the control, except for the first campaign when the treatments were not applied yet. Mean daytime conditions over the full 5–7 d campaigns were selected instead of instantaneous air temperature during the measurements to compare results among treatments within each campaign without including temperature effects driven by daytime variability. Relative air humidity (RH) was set at 50% to reflect ambient conditions, except for 2019, when the vapor pressure deficit (VPD) was set to 1.5 kPa. In summer 2020, we performed consecutive A sat measurements on a subsample of trees in all climatic treatments to evaluate the impact of changing RH vs VPD in the LI‐6800: RH was either set at 50%, or VPD at 1.5 kPa on the same trees. We found no significant differences in A sat (data not shown). Thus, we assume that the setting differences among 2019, 2020 and 2021 had no impact on our measurements. Leaf temperature was estimated using the instrument's energy balance calculations. Measurements were recorded after steady‐state gas exchange rates had been maintained for at least 5 min. After each measurement, the part of the leaf enclosed in the cuvette was harvested if it was smaller than the chamber (i.e. 6 cm2 in 2019 and 2020, and 2 cm2 in 2021), and the projected leaf area, which was used to correct recorded values, was measured using a flatbed scanner (Epson Perfection V800 Photo; Epson, Amsterdam, the Netherlands).

A sat was extracted from the first point of the A/C i curves at 400 ppm of CO2 concentration. Vcmax and J max were determined by fitting the A/C i curves using the Farquhar model for photosynthesis (Sharkey et al., 2007) and the plantecophys package (Duursma, 2015). Before fitting and after removing obvious outliers, curves were selected if they reached at least 600 ppm of C i and had a minimum of five data points. The default fitting methods of the plantecophys package were used to determine Vcmax and J max. The model used the temperature conditions applied in the cuvette. Nonfitting curves were removed from the data, leading to a total of 787 out of the 864 measured curves over the 3 yr with an average of 12 points per curve.

Dark‐adapted fluorescence

Directly after the A/C i measurements, the maximum photochemical efficiency (F v/F m) was measured on an adjacent leaf using the LI‐COR 6800 infrared gas analyzer system. Leaves were maintained in darkness using aluminum foil for at least 30 min before the measurements. Parameter settings were the same as for the A/C i curves described earlier, except for the CO2 concentration, which was kept at 400 ppm. The initial fluorescence (F 0) and maximum fluorescence value (F m) were measured using a saturating pulse of bright red light (8000 μmol quanta m−2 s−1 PAR, 1000 ms pulse width). The variable fluorescence (F v) was calculated by subtracting F 0 from F m.

Chlorophyll concentration

Chlorophyll concentration (Chl, in μmol m−2) was measured on the same leaves as those used for A/C i measurements with a chlorophyll concentration meter (MC‐100; Apogee Instruments Inc., Logan, UT, USA).

Statistical analysis

The response of A sat, Vcmax, J max, F v/F m, and Chl to the climatic treatments and species interactions was determined through linear mixed‐effects models for each species. The interactive effects of warming (yes/no), soil moisture reduction (yes/no), year (2019, 2020, 2021), and growing season stages (early, middle, late) were used as fixed effects. The test was performed first only on trees in intra‐specific interactions, and an additional interactive effect of the interaction (intra‐ vs inter‐specific) was added to the fixed effect to determine the impact of species interactions on the full dataset. The individual chambers were treated as a random effect. Tukey type post hoc tests were used to reveal significant differences between treatments for each measurement campaign (multcomp function).

To determine the impact of air temperature and soil moisture reduction on photosynthetic responses, the relationships between A sat, Vcmax, J max, F v/F m, and Chl in the intra‐specific interaction treatment and the daily air temperature or soil moisture content (i.e. during the same day as the measurements) were determined through Pearson's correlation test (cor.test function) across all climatic treatments and for each species.

All analyses were performed using the R v.3.6.1 statistical platform (R Development Core Team, Vienna, Austria, 2019).

Results

Warming and soil moisture reduction impacts in intra‐specific treatments

We found no effect of warming (W) on most photosynthetic properties of beech, besides that W significantly reduce the light‐saturated assimilation (A sat) in the last year of measurements and increased the maximum carboxylation rate (Vcmax), but only at one time in the middle of the growing season in 2019 (Supporting Information Table S1; Fig. 3). For oak, W had a positive impact on photosynthetic properties, resulting in increased Vcmax and maximum photosynthetic electron transport rate (J max) in 2020 (Table S2; Fig. 3).

Fig. 3.

Fig. 3

Open in a new tab

Light‐saturated assimilation (A sat), maximum carboxylation rate (Vcmax), maximum photosynthetic electron transport rate (J max), maximum photochemical efficiency (F v/F m), and chlorophyll concentration (Chl) for each measurement campaign (i.e. early, middle, and late growing season of 2019, 2020, and 2021, mean ± SE, n = 6 trees) and year (i.e. 2019, 2020, and 2021, mean ± SE, n = 18 trees) for beech (squares) and oak (circles) trees growing under control (blue), soil moisture reduction (gray), warming (orange), and warming + soil moisture reduction (purple) in the intra‐specific treatments. The black arrows indicate the onset of the climatic treatment. Significant differences between climatic treatments and the control are highlighted per campaign and species, and per year using a linear mixed‐effects models followed by a Tukey type post hoc test (*, 0.05  ≥ P  >  0.01; **, 0.01 ≥ P > 0.001; ***, P ≥ 0.001).

We found a significant reduction of A sat, Vcmax, J max and the chlorophyll concentration (Chl) in 2021 for beech in response to soil moisture reduction (MR). We also observed a significant decrease in the maximum photochemical efficiency (F v/F m) in 2020 for beech (Table S1; Fig. 3). For oak, we found a significant decline of A sat in 2020 and 2021, Vcmax and J max in 2020, F v/F m in 2019, and Chl in 2019 and 2020 (Table S2; Fig. 3) in response to MR.

Under combined warming and soil moisture reduction (WMR), we found similar reduction in A sat compared to trees exposed to MR alone for beech (in 2020 and 2021). We also observed a significant decrease in Vcmax and J max in 2019 and 2021, F v/F m in 2021, and Chl in 2020 depending on the campaign for beech (Table S1; Fig. 3). For oak, WMR had similar impacts as MR only. Indeed, we found a reduction of A sat and J max in 2020 and 2021, and Chl in 2020 in response to combined impacts (Table S2; Fig. 3) but no exacerbated effects were found.

Responses of photosynthetic properties to air temperature and soil water content in intra‐specific treatments

With an increase in daily air temperature, beech had significantly lower F v/F m (r 2 = 0.21 and P = 0.002) and Chl (r 2 = 0.30 and P < 0.001) (Fig. 4). For beech, no other relationship was found between the photosynthetic properties and daily air temperature. Oak showed an increase in A sat (r 2 = 0.16 and P = 0.016), Vcmax (r 2 = 0.36 and P < 0.001), and F v/F m (r 2 = 0.20 and P = 0.003) when daily air temperatures increased (Fig. 4). No relationship between Chl and the daily air temperature was found for oak.

Fig. 4.

Fig. 4

Open in a new tab

Relationships between the light‐saturated assimilation (A sat), maximum carboxylation rate (Vcmax), maximum photosynthetic electron transport rate (J max), maximum photochemical efficiency (F v/F m), and chlorophyll concentration (Chl) as a function of the daily air temperature (°C) for each measurement for beech (squares) and oak (circles) growing under control (blue), soil moisture reduction (gray), warming (orange), and warming + soil moisture reduction (purple) in the intra‐specific treatments. Significant regression lines across all treatments for each species are shown using a Pearson's correlation test (*, 0.05  ≥ P  >  0.01; **, 0.01 ≥ P > 0.001; ***, P ≥ 0.001).

With a decrease in daily soil water content, beech had a significantly lower A sat (r 2 = 0.43 and P < 0.001), Vcmax (r 2 = 0.25 and P < 0.001), J max (r 2 = 0.28 and P < 0.001), and F v/F m (r 2 = 0.23 and P = 0.009) (Fig. 5). No relationship between Chl and soil water content was found in beech. Oak showed a significant decrease in all photosynthetic properties, including A sat (r 2 = 0.50 and P < 0.001), Vcmax (r 2 = 0.43 and P < 0.001), J max (r 2 = 0.47 and P < 0.001), F v/F m (r 2 = 0.24 and P = 0.003), and Chl (r 2 = 0.42 and P < 0.001), when the daily soil water content decreased (Fig. 5).

Fig. 5.

Fig. 5

Open in a new tab

Relationships between the light‐saturated assimilation (A sat), maximum carboxylation rate (Vcmax), maximum photosynthetic electron transport rate (J max), maximum photochemical efficiency (F v/F m), and chlorophyll concentration (Chl) as a function of the daily soil water content (SWC, %) for each measurement for beech (squares) and oak (circles) growing under control (blue), soil moisture reduction (gray), warming (orange), and warming + soil moisture reduction (purple) in the intra‐specific treatments. Significant regression lines across all treatments for each species are shown using a Pearson's correlation test (*, 0.05  ≥ P  >  0.01; **, 0.01 ≥ P > 0.001; ***, P ≥ 0.001).

Warming and soil moisture reduction impacts in intra‐ vs inter‐specific interactions

In W conditions, we found no impact of species interactions on the photosynthetic properties of beech (Table S3; Fig. 6). For oak, trees in inter‐specific compositions had a lower J max compared to trees in intra‐specific compositions in early 2020 (Table S4; Fig. 6).

Fig. 6.

Fig. 6

Open in a new tab

Differences of light‐saturated assimilation (A sat), maximum carboxylation rate (Vcmax), maximum photosynthetic electron transport rate (J max), maximum photochemical efficiency (F v/F m), and chlorophyll concentration (Chl) for each measurement campaign (i.e. early, middle, and late growing season of 2019, 2020, and 2021, mean ± SE, n = 6 trees) and year (i.e. 2019, 2020, and 2021, mean ± SE, n = 18 trees) for beech (squares) and oak (circles) trees growing under control (blue), soil moisture reduction (gray), warming (orange), and warming + soil moisture reduction (purple) in the inter‐specific compositions compare to the intra‐specific treatments. Positive values indicate higher physiological rates in the inter‐specific treatments compared to the intra‐specific treatments. The black arrows indicate the onset of the climatic treatment. Significant differences between inter‐specific and intra‐specific treatments are highlighted per treatments, campaign and species using a linear mixed‐effects models followed by a Tukey type post hoc test (*, 0.05  ≥ P  >  0.01; **, 0.01 ≥ P > 0.001; ***, P ≥ 0.001).

In MR conditions, we found no impact of species interactions on the photosynthetic properties of both species (Tables S3, S4; Fig. 6).

In WMR conditions, we found that species interactions altered the photosynthetic properties of oak but not beech (Tables S3, S4; Fig. 6). For oak, we found that A sat, Vcmax, J max, and Chl were consistently higher in inter‐ vs intra‐specific compositions in 2020 and 2021 (only in 2021 for Vcmax), suggesting a mitigating effect of the interaction with beech under the most extreme climatic conditions.

Discussion

Warming and soil moisture reduction impacts in intra‐specific composition

As we initially expected, warming had opposite effects depending on the species. Beech leaf‐level light‐saturated assimilation (A sat) was negatively impacted by a chronic warming of +5°C during the last year of treatment exposure (Figs 3, 4). Biochemical limitations may have partially driven this effect as we observed a negative relationship between maximum photochemical efficiency (F v/F m), chlorophyll concentration (Chl) and air temperature (Fig. 4). However, no severe warming impact was observed on other leaf‐level photosynthetic properties, suggesting that the response of CO2 uptake to temperature must be driven primarily by stomatal limitation. Increased air temperature leads to a rise in VPD, which restricts stomatal conductance during warm days (Lendzion & Leuschner, 2008; Ambrose et al., 2016), thereby resulting in a lower assimilation. In our study, VPD frequently reached values above 3 kPa during the day (Fig. 2), especially in the warming treatment, which should lead to important stomatal restrictions (Grossiord et al., 2020). Furthermore, we found that stomatal conductance (g s) was severely reduced in the warming treatment compared to the control (Fig. S1), supporting our hypothesis about stomatal limitation. Moreover, Holišová et al. (2013) showed that beech has an optimal foliar temperature of about 24.5°C for A sat. We observed a mean air temperature of around 29°C between 09:00 and 16:00 h in the middle of the growing season (i.e. July and August) in the warming treatment, suggesting that heat stress could have contributed to reduced A sat.

On the contrary, oak trees benefited from warming already during the second year, where an increase in the leaf‐level maximum carboxylation rate (Vcmax) and maximum photosynthetic electron transport rate (J max) was observed (Figs 3, 4). Furthermore, a positive relationship was found between A sat, Vcmax, F v/F m and air temperature (Fig. 4). However, although these photosynthetic properties increased, enhanced temperature‐induced photosynthetic responses did not result in higher A sat in the warming treatment. We also observed that g s was not reduced by warming (Fig. S1), suggesting that stomatal limitation did not occur in this treatment for oak. Nonstomatal acclimation processes such as a higher CO2 diffusion through the mesophyll cells may partially explain this response: increased mesophyll conductance has been observed under warmer conditions (Bernacchi et al., 2002), but these responses are strongly variable across species. Von Caemmerer & Evans (2015) showed that Engelmann oak (Quercus engelmannii Greene.) shows a strong activation of the membrane diffusion with an increase in temperature. Thus, increased mesophyll conductance with higher temperature facilitates CO2 diffusion to the chloroplast and might therefore drive our higher carboxylation rates in downy oak. Furthermore, we found that the ratio between J max and Vcmax was lower in the warming treatment (Fig. S2), suggesting that trees grown at warmer temperatures tended to acclimate for the optimum temperature of J max and Vcmax (Kattge & Knorr, 2007). Overall, our findings suggest that beech will suffer from a warming atmosphere (Šimpraga et al., 2011; Holišová et al., 2013), while oak may benefit from temperature rise in temperate climates where heat stress is not yet limiting this species (Arend et al., 2013; Kuster et al., 2014). As shown in our study, photosynthetic responses to chronic warming are highly dependent of local climatic conditions and species' origin. The same experiment conducted in warmer or colder climates may lead to contrasting results with either stronger reductions or increases in photosynthesis depending on the temperature tolerance of the studied species (e.g. Stojnić et al., 2015).

Contrary to warming impacts and in accordance to our expectations, we found strong adverse soil moisture reduction effects for both species, particularly during the last year of measurements and most pronounced for beech (Figs 3, 5). This finding confirms many studies showing that drought negatively affects carbon assimilation and that beech is generally more affected than oak (Epron & Dreyer, 1993; Bréda et al., 2006; Gallé & Feller, 2007; Santos et al., 2018). Our results showed that both species had a lower A sat, Vcmax, J max, F v/F m, and Chl under moisture reduction conditions (Figs 3, 5). This finding suggests that reduced A sat might be driven by a combination of stomatal and nonstomatal limitation, as previously observed in several studies conducted on this species (e.g. Arend et al., 2013). Nonstomatal limitation might be attributed to a reduction in mesophyll conductance (e.g. Hommel et al., 2014) or anatomical changes (e.g. smaller and higher density of stomata; Schuldt et al., 2016; Tognetti et al., 1995). Further work investigating leaf anatomical, diffusional, and hydraulic changes would be needed to fully understand how prolonged moisture reduction impacted the photosynthetic properties of our trees.

Interestingly, a similar response in most photosynthetic properties was observed in response to moisture reduction acting alone and under combined warming (Fig. 3), indicating that water resource has a more important role in the photosynthetic response of our species than temperature. These results further reinforce previous work in which combined heat and drought negatively impacted leaf‐level photosynthetic properties but without additive effects (e.g. Rennenberg et al., 2006; Arend et al., 2013). Similar results have also been observed in piñon pine were foliar traits responded to drier conditions and where additional warming did not exacerbate these responses (Grossiord et al., 2017). For oak, the absence of additive effects and the overreaching impact of soil moisture could be driven by compensation mechanisms between temperature and soil water shortage as warming increased most photosynthetic properties (Fig. 5), while reduced moisture impaired them. Moreover, as downy oak is adapted to drought stress, physiological characteristics may be more responsive to changes in soil water availability. Furthermore, warming in our experiment may not have been experienced as a stressful factor for oak trees as the temperature range during the middle of the growing season (i.e. average of 29°C between 09:00 and 16:00 h for July and August) fell well within the thermal breadth of photosynthesis for this species (Warren, 2006). Further experiments on how warming and reduced soil moisture will impact photosynthesis would be needed to understand the consequences of our findings at the whole tree scale. Indeed, temperature and drought can modify plant allometry (Lines et al., 2012; Eziz et al., 2017), which could further enhance trends found at the leaf‐level. We observed that height and diameter increment were severely reduced for both species in the combined warming and soil moisture reduction treatment compared to the control (Fig. S3), suggesting lower leaf area and potentially stronger reductions in gas exchange at the tree level. However, further work including aboveground and belowground biomass assessment would be needed to draw solid conclusions on the carbon sequestration and allocation of these trees. Moreover, it is important to point out that we observed strong year‐to‐year variability in photosynthetic properties for both species, highlighting that both ontogeny and inter‐annual climatic variations are significant drivers of leaf photosynthetic responses to stress (Bréda & Granier, 1996; Verbeeck et al., 2008; Wang et al., 2008). Variability in photosynthesis and in photosynthetic capacity is commonly observed even if it is still rarely included in mechanistic models, which tend to use constant values per species. For instance, Wilson et al. (2001) demonstrated that neglecting the inter‐annual variations could results in an overestimate of the carbon exchange by around 50%. Hence, these warming and low soil moisture‐driven physiological changes are particularly relevant properties to be better incorporated in mechanistic plant physiological models.

Impact of species interactions on photosynthetic responses to warming and soil moisture reduction

Tree species interactions altered the photosynthetic responses to the climatic treatments, but mainly for oak and most strongly under extreme conditions (i.e. combined warming and moisture reduction). We initially expected beech and oak trees to both exhibit beneficial effects of their interaction because of their different functional strategies for resource uptake, such as light and water, which should lead to reduced competition for resources (e.g. Jonard et al., 2011; Zapater et al., 2011; Pretzsch et al., 2013). Yet, for beech, we found no changes between intra‐ and inter‐specific interactions in all climatic treatments, suggesting that the identity of their neighbors did not influence their response to environmental variability. This result contradicts many studies suggesting that species interactions and increased diversity could improve the photosynthetic properties of trees under low moisture conditions (Raftoyannis, 2002; Goisser et al., 2016; Metz et al., 2016) and reduce abiotic stress in combined warming and drought (e.g. de Andrés et al., 2017). The absence of response could be explained by the short time period of the experiment. Indeed, our trees are still at an early development stage (i.e. 5 yr old), and interactions between trees can take multiple years to establish (Domisch et al., 2015; Haase et al., 2015), especially belowground (Grossiord et al., 2014a,b,c) where water resource partitioning could be a primary mechanism driving mitigating effects of species interactions.

Nevertheless, our results highlighted a positive effect of inter‐specific interactions for oak, mainly under combined warming and reduced moisture (Fig. 6). This finding reinforces and complements previous studies suggesting that the interaction between the two tree species leads to beneficial carbon uptake processes during extreme events (Grossiord et al., 2015; Pardos et al., 2021). For instance, in a Mediterranean oak forest, Grossiord et al. (2014a,b,c) showed that turkey oak benefited from being in mixture with sessile oak by having less strong reductions in sap flux during dry periods compared to monoculture stands. Similarly, Forrester et al. (2016) showed that not necessarily all species benefit from species interactions, and that the beneficial effect of mixture strongly depends on the species and climatic conditions. In our case, the presence of beech trees could have reduced soil water competition for oak during hot and dry conditions as beech had lower carbon assimilation and transpiration rates than oak. Moreover, reduced shading in aboveground compartments could have benefited oak trees when mixed with beech as this species tends to grow in full sun light conditions. Indeed, the relatively strong light inside the OTCs may have been detrimental to beech seedlings, which are known to be shade‐tolerant and are normally growing under low light conditions in the understory (e.g. Ferrio et al., 2009), and could have contributed to the low photosynthetic properties observed in intra‐specific conditions (e.g. F v/F m, Fig. 3). However, we can only speculate about these underlying processes and further analyses on soil properties (e.g. nutrient content, decomposition rates), aboveground and belowground biomass and hydraulic traits would be needed to disentangle potential complementarity, facilitation and selection effects taking place in our study.

Conclusion

Our study highlights that European beech will likely suffer from an air temperature rise of +5°C, leading to impaired leaf‐level photosynthetic properties, independently of soil moisture. On the contrary, downy oak will probably benefit from prolonged warming by taking advantage of a more efficient photosynthetic responses, which could enhance CO2 uptake as long as soil moisture is not limiting. However, the beneficial effect of warming on the photosynthetic properties of oak quickly disappeared when warming co‐occurred with low soil moisture. Moreover, we show that interactions between beech and oak can further limit the adverse effects of warmer and drier soils for oak, suggesting that this species might be less vulnerable to future conditions in mixed‐species stands compared to monocultures.

Author contributions

MD‐G and CG conceived and designed the study; MS and JG provided and managed the OTC facility and implemented measurement and control systems; MD‐G and CG collected the data; MD‐G analyzed the data and led the writing of the manuscript; MD‐G, CG, AG, NB, MS and JG critically contributed to the manuscript and gave final approval for publication.

Supporting information

Fig. S1 Light‐saturated stomatal conductance for each measurement campaign and year for beech and oak trees growing under control, soil moisture reduction, warming, and warming + soil moisture reduction in the intra‐specific treatments.

Fig. S2 Thermal acclimation for beech and oak trees growing under control, soil moisture reduction, warming, and warming + soil moisture reduction in intra‐specific treatments.

Fig. S3 Growth traits for beech and oak trees growing under control, soil moisture reduction, warming, and warming + soil moisture reduction in intra‐specific treatments.

Table S1 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, and growing season stage evaluated on the measured traits for beech trees in intra‐specific treatments.

Table S2 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, and growing season stage evaluated on the measured traits for oak trees in intra‐specific treatments.

Table S3 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, growing season stage, and interaction (i.e. intra‐specific + inter‐specific) evaluated on the measured traits for beech trees.

Table S4 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, growing season stage, and interaction (i.e. intra‐specific + inter‐specific) evaluated on the measured traits for oak trees.

Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

Click here for additional data file. (580.6KB, pdf)

Acknowledgements

MD‐G and CG were supported by the Swiss National Science Foundation SNF (PZ00P3_174068 and 310030_204697). CG was further supported by the Sandoz Family Foundation. The authors are grateful to Eugénie Mas and Perrine Desvéronnières for their contribution with the data collection. Open access funding provided by ETH‐Bereich Forschungsanstalten.

Data availability

Data used in this manuscript is available from the Dryad Digital Repository, https://doi.org/10.5061/dryad.2bvq83bt1 (Didion‐Gency et al., 2021).

References

  1. Ambrose AR, Baxter WL, Wong CS, Burgess SSO, Williams CB, Næsborg RR, Koch GW, Dawson TE. 2016. Hydraulic constraints modify optimal photosynthetic profiles in giant sequoia trees. Oecologia 182: 713–730. [DOI] [PubMed] [Google Scholar]
  2. Anderegg WRL, Konings AG, Trugman AT, Yu K, Bowling DR, Gabbitas R, Karp DS, Pacala S, Sperry JS, Sulman BN et al. 2018. Hydraulic diversity of forests regulates ecosystem resilience during drought. Nature 561: 538–541. [DOI] [PubMed] [Google Scholar]
  3. de Andrés E, Seely B, Blanco JA, Imbert JB, Lo Y‐H, Castillo FJ. 2017. Increased complementarity in water‐limited environments in Scots pine and European beech mixtures under climate change: climate change increases complementarity in pine/beech mixedwoods. Ecohydrology 10: e1810. [Google Scholar]
  4. Arend M, Brem A, Kuster TM, Günthardt‐Goerg MS. 2013. Seasonal photosynthetic responses of European oaks to drought and elevated daytime temperature: photosynthetic responses to drought and elevated temperature. Plant Biology 15: 169–176. [DOI] [PubMed] [Google Scholar]
  5. Arend M, Kuster T, Gunthardt‐Goerg MS, Dobbertin M. 2011. Provenance‐specific growth responses to drought and air warming in three European oak species (Quercus robur, Q. petraea and Q. pubescens). Tree Physiology 31: 287–297. [DOI] [PubMed] [Google Scholar]
  6. Arend M, Sever K, Pflug E, Gessler A, Schaub M. 2016. Seasonal photosynthetic response of European beech to severe summer drought: limitation, recovery and post‐drought stimulation. Agricultural and Forest Meteorology 220: 83–89. [Google Scholar]
  7. Bernacchi CJ, Portis AR, Nakano H, von Caemmerer S, Long SP. 2002. Temperature response of mesophyll conductance. Implications for the determination of rubisco enzyme kinetics and for limitations to photosynthesis in vivo . Plant Physiology 130: 1992–1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bréda N, Granier A. 1996. Intra‐ and interannual variations of transpiration, leaf area index and radial growth of a sessile oak stand (Quercus petraea). Annales Des Sciences Forestières 53: 521–536. [Google Scholar]
  9. Bréda N, Huc R, Granier A, Dreyer E. 2006. Temperate forest trees and stands under severe drought: a review of ecophysiological responses, adaptation processes and long‐term consequences. Annals of Forest Science 63: 625–644. [Google Scholar]
  10. von Caemmerer S, Evans J. 2015. Temperature responses of mesophyll conductance differ greatly between species: temperature responses of mesophyll conductance. Plant, Cell & Environment 38: 629–637. [DOI] [PubMed] [Google Scholar]
  11. Ciais P, Reichstein M, Viovy N, Granier A, Ogée J, Allard V, Aubinet M, Buchmann N, Bernhofer C, Carrara A et al. 2005. Europe‐wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437: 529–533. [DOI] [PubMed] [Google Scholar]
  12. Contran N, Günthardt‐Goerg MS, Kuster TM, Cerana R, Crosti P, Paoletti E. 2013. Physiological and biochemical responses of Quercus pubescens to air warming and drought on acidic and calcareous soils: responses of Quercus to air warming, drought and soil pH. Plant Biology 15: 157–168. [DOI] [PubMed] [Google Scholar]
  13. Dai L, Xu Y, Harmens H, Duan H, Feng Z, Hayes F, Sharps K, Radbourne A, Tarvainen L. 2021. Reduced photosynthetic thermal acclimation capacity under elevated ozone in poplar (Populus tremula) saplings. Global Change Biology 27: 2159–2173. [DOI] [PubMed] [Google Scholar]
  14. Didion‐Gency M, Bachofen C, Buchmann N, Gessler A, Morin X, Vicente E, Vollenweider P, Grossiord C. 2021. Interactive effects of tree species mixture and climate on foliar and woody trait variation in a widely distributed deciduous tree. Functional Ecology 35: 2397–2408. [Google Scholar]
  15. Domisch T, Finér L, Dawud SM, Vesterdal L, Raulund‐Rasmussen K. 2015. Does species richness affect fine root biomass and production in young forest plantations? Oecologia 177: 581–594. [DOI] [PubMed] [Google Scholar]
  16. Dreyer E, Le Roux X, Montpied P, Daudet FA, Masson F. 2001. Temperature response of leaf photosynthetic capacity in seedlings from seven temperate tree species. Tree Physiology 21: 223–232. [DOI] [PubMed] [Google Scholar]
  17. Durrant TH, de Rigo D, Caudullo G. 2016. Fagus sylvatica in Europe: distribution, habitat, usage and threats. In: San‐Miguel‐Ayanz J, de Rigo D, Caudullo G, Houston Durrant T, Mauri A, eds. European atlas of forest tree species. Luxembourg, Europe: European Commission. [WWW document] URL https://w3id.org/mtv/FISE‐Comm/v01/e012b90 [accessed 25 July 2022]. [Google Scholar]
  18. Dusenge ME, Duarte AG, Way DA. 2019. Plant carbon metabolism and climate change: elevated CO2 and temperature impacts on photosynthesis, photorespiration and respiration. New Phytologist 221: 32–49. [DOI] [PubMed] [Google Scholar]
  19. Dusenge ME, Wittemann M, Mujawamariya M, Ntawuhiganayo EB, Zibera E, Ntirugulirwa B, Way DA, Nsabimana D, Uddling J, Wallin G. 2021. Limited thermal acclimation of photosynthesis in tropical montane tree species. Global Change Biology 27: 4860–4878. [DOI] [PubMed] [Google Scholar]
  20. Duursma RA. 2015. Plantcophys ‐ an R package for analysing and modelling leaf gas exchange data. PLoS ONE 10: e0143346. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Epron D, Dreyer E. 1993. Long‐term effects of drought on photosynthesis of adult oak trees (Quercus petraea (Matt.) Liebl. and Quercus robur L.) in a natural stand. New Phytologist 125: 381–389. [DOI] [PubMed] [Google Scholar]
  22. Eziz A, Yan Z, Tian D, Han W, Tang Z, Fang J. 2017. Drought effect on plant biomass allocation: a meta‐analysis. Ecology and Evolution 7: 11002–11010. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Ferrio JP, Cuntz M, Offermann C, Siegwolf R, Saurer M, Gessler A. 2009. Effect of water availability on leaf water isotopic enrichment in beech seedlings shows limitations of current fractionation models. Plant, Cell & Environment 32: 1285–1296. [DOI] [PubMed] [Google Scholar]
  24. Flexas J, Medrano H. 2002. Drought‐inhibition of Photosynthesis in C3 Plants: stomatal and non‐stomatal limitations revisited. Annals of Botany 89: 183–189. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Forrester DI, Bonal D, Dawud S, Gessler A, Granier A, Pollastrini M, Grossiord C. 2016. Drought responses by individual tree species are not often correlated with tree species diversity in European forests. Journal of Applied Ecology 53: 1725–1734. [Google Scholar]
  26. Gallé A, Feller U. 2007. Changes of photosynthetic traits in beech saplings (Fagus sylvatica) under severe drought stress and during recovery. Physiologia Plantarum 131: 412–421. [DOI] [PubMed] [Google Scholar]
  27. Gessler A, Keitel C, Kreuzwieser J, Matyssek R, Seiler W, Rennenberg H. 2006. Potential risks for European beech (Fagus sylvatica L.) in a changing climate. Trees 21: 1–11. [Google Scholar]
  28. Gessler A, Schaub M, McDowell NG. 2017. The role of nutrients in drought‐induced tree mortality and recovery. New Phytologist 214: 513–520. [DOI] [PubMed] [Google Scholar]
  29. Gillespie LM, Fromin N, Milcu A, Buatois B, Pontoizeau C, Hättenschwiler S. 2020. Higher tree diversity increases soil microbial resistance to drought. Communications Biology 3: 377. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Goisser M, Geppert U, Rötzer T, Paya A, Huber A, Kerner R, Bauerle T, Pretzsch H, Pritsch K, Häberle KH et al. 2016. Does belowground interaction with Fagus sylvatica increase drought susceptibility of photosynthesis and stem growth in Picea abies? Forest Ecology and Management 375: 268–278. [Google Scholar]
  31. Gounaris K, Brain ARR, Quinn PJ, Williams WP. 1984. Structural reorganisation of chloroplast thylakoid membranes in response to heat‐stress. Biochimica et Biophysica Acta (BBA) – Bioenergetics 766: 198–208. [Google Scholar]
  32. Grossiord C. 2019. Having the right neighbors: how tree species diversity modulates drought impacts on forests. New Phytologist 228: 42–49. [DOI] [PubMed] [Google Scholar]
  33. Grossiord C, Bachofen C, Gisler J, Mas E, Vitasse V, Didion‐Gency M. 2022. Warming may extend tree growing seasons and compensate for reduced carbon uptake during dry periods. Journal of Ecology 48: 1575–1589. [Google Scholar]
  34. Grossiord C, Forner A, Gessler A, Granier A, Pollastrini M, Valladares F, Bonal D. 2015. Influence of species interactions on transpiration of Mediterranean tree species during a summer drought. European Journal of Forest Research 134: 365–376. [Google Scholar]
  35. Grossiord C, Gessler A, Granier A, Berger S, Bréchet C, Hentschel R, Hommel R, Scherer‐Lorenzen M, Bonal D. 2014a. Impact of interspecific interactions on the soil water uptake depth in a young temperate mixed species plantation. Journal of Hydrology 519: 3511–3519. [Google Scholar]
  36. Grossiord C, Gessler A, Granier A, Pollastrini M, Bussotti F, Bonal D. 2014b. Interspecific competition influences the response of oak transpiration to increasing drought stress in a mixed Mediterranean forest. Forest Ecology and Management 318: 54–61. [Google Scholar]
  37. Grossiord C, Granier A, Ratcliffe S, Bouriaud O, Bruelheide H, Checko E, Forrester DI, Dawud SM, Finer L, Pollastrini M et al. 2014c. Tree diversity does not always improve resistance of forest ecosystems to drought. Proceedings of the National Academy of Sciences, USA 111: 14812–14815. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Grossiord C, Sevanto S, Adams HD, Collins AD, Dickman LT, McBranch N, Michaletz ST, Stockton EA, Vigil M, McDowell NG. 2017. Precipitation, not air temperature, drives functional responses of trees in semi‐arid ecosystems. Journal of Ecology 105: 163–175. [Google Scholar]
  39. Grossiord C, Ulrich DEM, Vilagrosa A. 2020. Controls of the hydraulic safety‐efficiency trade‐off. Tree Physiology 40: 573–576. [DOI] [PubMed] [Google Scholar]
  40. Haase J, Castagneyrol B, Cornelissen JHC, Ghazoul J, Kattge J, Koricheva J, Scherer‐Lorenzen M, Morath S, Jactel H. 2015. Contrasting effects of tree diversity on young tree growth and resistance to insect herbivores across three biodiversity experiments. Oikos 124: 1674–1685. [Google Scholar]
  41. Holišová P, Šigut L, Klem K, Urban O. 2013. Growth under elevated CO2 concentration affects the temperature response of photosynthetic rate. Beskydy 6: 43–52. [Google Scholar]
  42. Hommel R, Siegwolf R, Saurer M, Farquhar GD, Kayler Z, Ferrio JP, Gessler A. 2014. Drought response of mesophyll conductance in forest understory species—impacts on water‐use efficiency and interactions with leaf water movement. Physiologia Plantarum 152: 98–114. [DOI] [PubMed] [Google Scholar]
  43. Hooper DU, Chapin FS, Ewel JJ, Hector A, Inchausti P, Lavorel S, Lawton JH, Lodge DM, Loreau M, Naeem S et al. 2005. Effects of biodiversity on ecosystem functioning: a consensur of current knowledge. Ecological Monographs 75: 3–35. [Google Scholar]
  44. Húdoková H, Petrik P, Petek‐Petrik A, Konôpková A, Leštianska A, Střelcová K, Kmeť J, Kurjak D. 2022. Heat‐stress response of photosystem II in five ecologically important tree species of European temperate forests. Biologia 77: 671–680. [Google Scholar]
  45. Jonard F, André F, Ponette Q, Vincke C, Jonard M. 2011. Sap flux density and stomatal conductance of European beech and common oak trees in pure and mixed stands during the summer drought of 2003. Journal of Hydrology 409: 371–381. [Google Scholar]
  46. Jourdan M, Piedallu C, Baudry J, Morin X. 2020. Tree diversity and the temporal stability of mountain forest productivity: testing the effect of species composition, through asynchrony and overyielding. European Journal of Forest Research 140: 273–286. [Google Scholar]
  47. Jucker T, Avăcăriței D, Bărnoaiea I, Duduman G, Bouriaud O, Coomes DA. 2016. Climate modulates the effects of tree diversity on forest productivity. Journal of Ecology 104: 388–398. [Google Scholar]
  48. Kattge J, Knorr W. 2007. Temperature acclimation in a biochemical model of photosynthesis: a reanalysis of data from 36 species. Plant, Cell & Environment 30: 1176–1190. [DOI] [PubMed] [Google Scholar]
  49. Klein T. 2014. The variability of stomatal sensitivity to leaf water potential across tree species indicates a continuum between isohydric and anisohydric behaviours. Functional Ecology 28: 1313–1320. [Google Scholar]
  50. Kothari S, Montgomery RA, Cavender‐Bares J. 2021. Physiological responses to light explain competition and facilitation in a tree diversity experiment. Journal of Ecology 109: 2000–2018. [Google Scholar]
  51. Kuster TM, Dobbertin M, Günthardt‐Goerg MS, Schaub M, Arend M. 2014. A phenological timetable of oak growth under experimental drought and air warming. PLoS ONE 9: e89724. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Lendzion J, Leuschner C. 2008. Growth of European beech (Fagus sylvatica L.) saplings is limited by elevated atmospheric vapour pressure deficits. Forest Ecology and Management 256: 648–655. [Google Scholar]
  53. Liang J, Zhou M, Tobin PC, McGuire AD, Reich PB. 2015. Biodiversity influences plant productivity through niche–efficiency. Proceedings of the National Academy of Sciences, USA 112: 5738–5743. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Lines ER, Zavala MA, Purves DW, Coomes DA. 2012. Predictable changes in aboveground allometry of trees along gradients of temperature, aridity and competition: predictable variation in tree aboveground allometry. Global Ecology and Biogeography 21: 1017–1028. [Google Scholar]
  55. Medlyn BE, Dreyer E, Ellsworth D, Forstreuter M, Harley PC, Kirschbaum MUF, Le Roux X, Montpied P, Strassemeyer J, Walcroft A et al. 2002. Temperature response of parameters of a biochemically based model of photosynthesis. II. A review of experimental data. Plant, Cell & Environment 25: 1167–1179. [Google Scholar]
  56. Mensah S, du Toit B, Seifert T. 2018. Diversity–biomass relationship across forest layers: implications for niche complementarity and selection effects. Oecologia 187: 783–795. [DOI] [PubMed] [Google Scholar]
  57. Metz J, Annighöfer P, Schall P, Zimmermann J, Kahl T, Schulze E‐D, Ammer C. 2016. Site‐adapted admixed tree species reduce drought susceptibility of mature European beech. Global Change Biology 22: 903–920. [DOI] [PubMed] [Google Scholar]
  58. Mittler R. 2006. Abiotic stress, the field environment and stress combination. Trends in Plant Science 11: 15–19. [DOI] [PubMed] [Google Scholar]
  59. Overpeck JT. 2013. The challenge of hot drought. Nature 503: 350–351. [DOI] [PubMed] [Google Scholar]
  60. Paquette A, Messier C. 2011. The effect of biodiversity on tree productivity: from temperate to boreal forests: the effect of biodiversity on the productivity. Global Ecology and Biogeography 20: 170–180. [Google Scholar]
  61. Pardos M, del Río M, Pretzsch H, Jactel H, Bielak K, Bravo F, Brazaitis G, Defossez E, Engel M, Godvod K et al. 2021. The greater resilience of mixed forests to drought mainly depends on their composition: analysis along a climate gradient across Europe. Forest Ecology and Management 481: 118687. [Google Scholar]
  62. Parry MAJ. 2002. Rubisco activity: effects of drought stress. Annals of Botany 89: 833–839. [DOI] [PMC free article] [PubMed] [Google Scholar]
  63. Pasta S, de Rigo D, & Caudullo G. 2016. Quercus pubescens in Europe: distribution, habitat, usage and threats. In: San‐Miguel‐Ayanz J, de Rigo D, Caudullo G, Houston Durrant T, Mauri A, eds. European Atlas of forest tree species. Luxembourg, Europe: European Commission. [WWW document] URL https://w3id.org/mtv/FISE‐Comm/v01/e019e5c [accessed 3 July 2022]. [Google Scholar]
  64. Powles SB. 1984. Photoinhibition of photosynthesis induced by visible light. Annual Review of Plant Biology 35: 15–44. [Google Scholar]
  65. Pretzsch H, Bielak K, Block J, Bruchwald A, Dieler J, Ehrhart H‐P, Kohnle U, Nagel J, Spellmann H, Zasada M et al. 2013. Productivity of mixed versus pure stands of oak (Quercus petraea (Matt.) Liebl. and Quercus robur L.) and European beech (Fagus sylvatica L.) along an ecological gradient. European Journal of Forest Research 132: 263–280. [Google Scholar]
  66. Prieto P, Peñuelas J, Llusià J, Asensio D, Estiarte M. 2009. Effects of long‐term experimental night‐time warming and drought on photosynthesis, F v/F m and stomatal conductance in the dominant species of a Mediterranean shrubland. Acta Physiologiae Plantarum 31: 729–739. [Google Scholar]
  67. Raftoyannis Y. 2002. Physiological responses of beech and sessile oak in a natural mixed stand during a dry summer. Annals of Botany 89: 723–730. [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Rebetez M, Mayer H, Dupont O, Schindler D, Gartner K, Kropp JP, Menzel A. 2006. Heat and drought 2003 in Europe: a climate synthesis. Annals of Forest Science 63: 569–577. [Google Scholar]
  69. Rennenberg H, Loreto F, Polle A, Brilli F, Fares S, Beniwal RS, Gessler A. 2006. Physiological responses of forest trees to heat and drought. Plant Biology 8: 556–571. [DOI] [PubMed] [Google Scholar]
  70. Rödenbeck C, Zaehle S, Keeling R, Heimann M. 2020. The European carbon cycle response to heat and drought as seen from atmospheric CO2 data for 1999–2018. Philosophical Transactions of the Royal Society B: Biological Sciences 375: 20190506. [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Santos VAHF d, Ferreira MJ, Rodrigues JVFC, Garcia MN, Ceron JVB, Nelson BW, Saleska SR. 2018. Causes of reduced leaf‐level photosynthesis during strong El Niño drought in a Central Amazon forest. Global Change Biology 24: 4266–4279. [DOI] [PubMed] [Google Scholar]
  72. Schönbeck L, Grossiord C, Gessler A, Gisler J, Meusburger K, D'Odorico P, Rigling A, Salmon Y, Stocker BD, Zweifel R et al. 2022. Photosynthetic acclimation and sensitivity to short‐ and long‐term environmental changes in a drought prone forest. Journal of Experimental Botany 73: 2576–2588. [DOI] [PubMed] [Google Scholar]
  73. Schönbeck L, Li M‐H, Lehmann MM, Rigling A, Schaub M, Hoch G, Kahmen A, Gessler A. 2021. Soil nutrient availability alters tree carbon allocation dynamics during drought. Tree Physiology 41: 697–707. [DOI] [PubMed] [Google Scholar]
  74. Schuldt B, Buras A, Arend M, Vitasse Y, Beierkuhnlein C, Damm A, Gharun M, Grams TEE, Hauck M, Hajek P et al. 2020. A first assessment of the impact of the extreme 2018 summer drought on Central European forests. Basic and Applied Ecology 45: 86–103. [Google Scholar]
  75. Schuldt B, Knutzen F, Delzon S, Jansen S, Müller‐Haubold H, Burlett R, Clough Y, Leuschner C. 2016. How adaptable is the hydraulic system of European beech in the face of climate change‐related precipitation reduction? New Phytologist 210: 443–458. [DOI] [PubMed] [Google Scholar]
  76. Sharkey TD, Bernacchi CJ, Farquhar GD, Singsaas EL. 2007. Fitting photosynthetic carbon dioxide response curves for C3 leaves. Plant, Cell & Environment 30: 1035–1040. [DOI] [PubMed] [Google Scholar]
  77. Šimpraga M, Verbeeck H, Demarcke M, Joó É, Amelynck C, Schoon N, Dewulf J, Van Langenhove H, Heinesch B, Aubinet M et al. 2011. Comparing monoterpenoid emissions and net photosynthesis of beech (Fagus sylvatica L.) in controlled and natural conditions. Atmospheric Environment 45: 2922–2928. [Google Scholar]
  78. 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. European Journal of Forest Research 134: 1109–1125. [Google Scholar]
  79. Sun CX, Huang GH, Fan Y, Zhou X, Lu C, Wang XQ. 2019. Drought occurring with hot extremes: changes under future climate change on loess plateau, China. Earth's Future 7: 587–604. [Google Scholar]
  80. Thomas FM. 2000. Growth and water relations of four deciduous tree species (Fagus sylvatica L., Quercus petraea (Matt.) Liebl., Q. pubescens Willd., Sorbus aria (L.) Cr.) occurring at Central‐European tree‐line sites on shallow calcareous soils: physiological reactions of seedlings to severe drought. Flora 195: 104–115. [Google Scholar]
  81. Tognetti R, Johnson JD, Michelozzi M. 1995. The response of European beech (Fagus sylvatica L.) seedlings from two Italian populations to drought and recovery. Trees 9: 348–354. [Google Scholar]
  82. Verbeeck H, Samson R, Granier A, Montpied P, Lemeur R. 2008. Multi‐year model analysis of GPP in a temperate beech forest in France. Ecological Modelling 210: 85–103. [Google Scholar]
  83. Wang Q, Iio A, Tenhunen J, Kakubari Y. 2008. Annual and seasonal variations in photosynthetic capacity of Fagus crenata along an elevation gradient in the Naeba Mountains, Japan. Tree Physiology 28: 277–285. [DOI] [PubMed] [Google Scholar]
  84. Warren C. 2006. Temperature response of photosynthesis and internal conductance to CO2: results from two independent approaches. Journal of Experimental Botany 57: 3057–3067. [DOI] [PubMed] [Google Scholar]
  85. Way DA, Oren R. 2010. Differential responses to changes in growth temperature between trees from different functional groups and biomes: a review and synthesis of data. Tree Physiology 30: 669–688. [DOI] [PubMed] [Google Scholar]
  86. Way DA, Oren R, Kroner Y. 2015. The space‐time continuum: the effects of elevated CO2 and temperature on trees and the importance of scaling. Plant, Cell & Environment 38: 991–1007. [DOI] [PubMed] [Google Scholar]
  87. Wilson KB, Baldocchi DD, Hanson PJ. 2001. Leaf age affects the seasonal pattern of photosynthetic capacityand net ecosystem exchange of carbon in a deciduous forest: leaf age and net ecosystem exchange of carbon. Plant, Cell & Environment 24: 571–583. [Google Scholar]
  88. Yamane Y, Kashino Y, Koike H, Satoh K. 1997. Increases in the fluorescence Fo level and reversible inhibition of Photosystem II reaction center by high‐temperature treatments in higher plants. Photosynthesis Research 52: 57–64. [Google Scholar]
  89. Zak DR, Holmes WE, White DC, Peacock AD, Tilman D. 2003. Plant diversity, soil microbial communities, and ecosystem function: are there any links ? Ecology 84: 2042–2050. [Google Scholar]
  90. Zapater M, Hossann C, Bréda N, Bréchet C, Bonal D, Granier A. 2011. Evidence of hydraulic lift in a young beech and oak mixed forest using 18O soil water labelling. Trees 25: 885–894. [Google Scholar]
  91. Zhou S, Medlyn B, Sabaté S, Sperlich D, Prentice IC, Whitehead D. 2014. Short‐term water stress impacts on stomatal, mesophyll and biochemical limitations to photosynthesis differ consistently among tree species from contrasting climates. Tree Physiology 34: 1035–1046. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Fig. S1 Light‐saturated stomatal conductance for each measurement campaign and year for beech and oak trees growing under control, soil moisture reduction, warming, and warming + soil moisture reduction in the intra‐specific treatments.

Fig. S2 Thermal acclimation for beech and oak trees growing under control, soil moisture reduction, warming, and warming + soil moisture reduction in intra‐specific treatments.

Fig. S3 Growth traits for beech and oak trees growing under control, soil moisture reduction, warming, and warming + soil moisture reduction in intra‐specific treatments.

Table S1 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, and growing season stage evaluated on the measured traits for beech trees in intra‐specific treatments.

Table S2 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, and growing season stage evaluated on the measured traits for oak trees in intra‐specific treatments.

Table S3 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, growing season stage, and interaction (i.e. intra‐specific + inter‐specific) evaluated on the measured traits for beech trees.

Table S4 Summary of the ANOVA tests of the linear mixed‐effects models with the interactive effects of warming, soil moisture reduction, year, growing season stage, and interaction (i.e. intra‐specific + inter‐specific) evaluated on the measured traits for oak trees.

Please note: Wiley Blackwell are not responsible for the content or functionality of any Supporting Information supplied by the authors. Any queries (other than missing material) should be directed to the New Phytologist Central Office.

Click here for additional data file. (580.6KB, pdf)

Data Availability Statement

Data used in this manuscript is available from the Dryad Digital Repository, https://doi.org/10.5061/dryad.2bvq83bt1 (Didion‐Gency et al., 2021).

Articles from The New Phytologist are provided here courtesy of Wiley

RESOURCES