# The effect of climate at origin on Douglas-fir growth, leaf traits and embolism resistance along a rainfall gradient in Central Europe

Vincent P. Riedel, Patrick Engel, Pierre-André Waite, Roman M. Link, Randolf Schirmer, Joachim Hamberger, Bernhard Schuldt

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## ► To cite this version:

Vincent P. Riedel, Patrick Engel, Pierre-André Waite, Roman M. Link, Randolf Schirmer, et al.. The effect of climate at origin on Douglas-fir growth, leaf traits and embolism resistance along a rainfall gradient in Central Europe. Trees - Structure and Function, 2025, 39, pp.42. 10.1007/s00468-025-02605-1. hal-05182989

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# The effect of climate at origin on Douglas-fir growth, leaf traits and embolism resistance along a rainfall gradient in Central Europe

Vincent P. Riedel<fnref n="1" />,<fnref n="2" />* · Patrick Engel<fnref n="1" /> · Pierre-André Waite<fnref n="4" /> · Roman M. Link<fnref n="1" />,<fnref n="2" /> · Randolf Schirmer<fnref n="3" /> · Joachim Hamberger<fnref n="3" /> · Bernhard Schuldt<fnref n="1" />,<fnref n="2" />

Received: 16 September 2024 / Accepted: 17 January 2025
© The Author(s) 2025

## Abstract

**Key message** In Douglas-fir grown in Central Europe, growth and specific leaf area differed between coastal and interior provenances but little intra-specific variability was found for the Huber value and xylem safety.

**Abstract** In Central Europe, the economically most important timber species for roundwood production, Norway spruce, has been severely affected by recent global change-type drought events. Due to its large spatial distribution, Douglas-fir (*Pseudotsuga menziesii*) is considered for conversion to climate-resilient forests. Specifically, provenances from moister coastal and drier and colder interior regions might differ in drought tolerance traits. Here, we characterized aboveground biomass increment as well as leaf morphological and plant hydraulic traits in mature trees of 28 Douglas-fir provenances from three climate-at-origin groups across a climatic gradient in Central Europe, covering a precipitation range of 542 mm yr⁻<fnref n="1" />. Irrespective of the gradient, the northern interior provenances had a 5.4 kg yr⁻<fnref n="1" /> lower aboveground biomass increment than the two coastal groups, accompanied by a 13% smaller specific leaf area. On the other hand, the Huber value, embolism resistance (*P*₅₀) and leaf carbon isotope signature (δ¹³C) as proxy for long-term intrinsic water use efficiency did not differ between climate-origin groups. Across the gradient and within a climate-origin-group, no effect of climatic aridity on any of the traits covered was observed. Especially *P*₅₀ showed very little intra-specific variability, and our observed mean of -3.5 MPa is in the same range as *P*₅₀-values for Douglas-fir recently reported from Europe. Our results for Douglas-fir support that xylem safety is a rather conservative and evolutionary canalized trait in conifers, while the Huber value revealed less plasticity as expected. Future studies are needed to test whether slower-growing interior provenances with thicker and smaller needles might be more drought tolerant and thus better suited for cultivation in the future climate of Central Europe although xylem safety does not differ.

**Keywords** Cavitation resistance · Huber value · Specific leaf area · Growth rate · Leaf carbon isotopic signature (δ¹³C) · Climatic gradient · Provenances · Plant hydraulic traits · Xylem safety

Communicated by Andrea Nardini.

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Vincent P. Riedel
vincent.riedel92@googlemail.com

## Introduction

Water in sufficient quantity and in the right thermodynamic state is essential for plant growth and survival. As a result, terrestrial plants have evolved complex systems for managing and conserving water. Because environmental conditions are not stable, plants employ a variety of adaptations in response to water deficit, including adjustments in vascular architecture, leaf morphology or physiology such as stoma-tal control. Together, these adaptations control plant water relations and determine drought resistance (Skelton et al. 2021; Gazol and Camarero 2022). Even within a single species, there can be considerable variation in adaptive traits for water conservation between populations from different

<footnote n="1">¹ Chair of Forest Botany, Technical University, Dresden, Germany</footnote>

<footnote n="2">² Chair of Ecophysiology and Vegetation Ecology, Julius-Maximilians-Universität Würzburg, Würzburg, Germany</footnote>

<footnote n="3">³ Forstgenetisches Versuchswesen, Bayrisches Amt für Waldgenetik, Germany</footnote>

<footnote n="4">⁴ Agroécologie et Intensification Durable des cultures Annuelles, Centre de coopération Internationale en Recherche Agronomique pour le Développement (CIRAD), Montpellier, France</footnote>
climatic zones (White 1987). The survival of species may increasingly depend on populations adapted to hotter and drier environments (Aitken et al. 2008). To develop climate-resilient forests, it is essential to investigate the extent to which specific populations vary in their ability to conserve and manage water resources in response to increasingly frequent drought events.

In the recent past, Central Europe has experienced rising temperatures and low precipitation sums (Buras et al. 2020; Rousi et al. 2022), and the frequency of compound drought and heatwave events is expected to increase dramatically (Bevacqua et al. 2022; Hari et al. 2020; Tripathy et al. 2023). In parallel, an increase in tree mortality has been observed in Central Europe (Schuldt et al. 2020; Schuldt & Ruehr 2022). Due to large-scale reforestation and economic considerations, Norway spruce (*Picea abies* (L.) H. KARST) has been the most abundant tree species in Germany for decades. However, recent heatwaves in combination with bark beetle calamities have strongly decimated its populations, making this species one of the most threatened in Central Europe (Krejza et al. 2021). As a result, there is a need for alternative tree species suited for roundwood production and with a lower drought vulnerability. Douglas-fir (*Pseudotsuga menziesii* (MIRB.) FRANCO) is a candidate that appears to meet these requirements, as it has a wide ecological amplitude at its place of origin in Northern America. Douglas-firs introduction to European Forest dates back to the 19th and 20th century and now accounts for an area of 0.40% (Spiecker et al. 2019). Its potential ability to remain productive under drought conditions makes it a particularly favored tree species for Central Europe (Konnert & Fussi 2012; Eilmann et al. 2013). Like most tree species with a wide natural range, Douglas-fir has a high genetic variability (Lavender and Hermann 2014; Bansal et al. 2016; Castaldi et al. 2020). Commonly, coastal Douglas-fir provenances (*P. menziesii. var. menziesii*) are preferred for planting across Europe compared to interior provenances (*P. menziesii. var. glauca*, *P. menziesii var. caesia*) because of their rapid growth and high resistance towards the fungus *Rhabdocline pseudotsugae* (Eilmann et al. 2013; Thomas et al. 2022). However, Niemczyk et al. (2021) found that interior provenances show better growth performance and survival in Poland, which aligns with the comparable continental climatic conditions between places of origin and cultivation. Furthermore, in the context of climate change and the observed and anticipated increase in extreme drought events, lower growth rates commonly associated with lower water use (cf., Kotowska et al. 2021) might be beneficial. Also, populations from areas of dry summers and cold winters are likely to be cold and drought tolerant (Laanisto & Niinemets 2015). Therefore, it is of great interest for both ecologists and forest managers to identify the degree of intra-specific trait variability of Douglas-fir in response to reduced water availability.

Hydraulic and leaf morphological traits have been widely used to quantify and compare drought-related performance within given tree species (Weithmann et al. 2022a, 2022b; Kurjak et al. 2024). Xylem vulnerability to water stress plays a significant role in drought-induced tree mortality (Adams et al. 2017; Hajek et al. 2022; Waite et al. 2024). Once species-specific water potential levels are reached, gas bubbles can form, causing embolism in the vascular system and significantly reducing water transport to the canopy (Choat et al. 2018). The survival of woody plants under drought conditions is therefore linked to the ability of avoiding excessive embolism formation (Martin-StPaul et al. 2017; Sapes et al. 2019). A xylem that is able to maintain hydraulic conductivity under more negative water potentials is classically considered to be more drought resistant (Sperry & Tyree 1988). To quantify this drought resistance, the xylem water potential at 50% loss of hydraulic conductance, i.e., the $P_{50}$-value, is commonly used to describe the xylem resistance to drought-induced hydraulic failure.

In response to climatic or edaphic aridity, woody species can either increase xylem safety as observed in European beech (Schuldt et al. 2016; Weithmann et al. 2022a), reduce their transpiring leaf surface area in order to improve single leaf water status as observed in Scots pine (Martinez-Vilalta et al. 2009), or adjust both. Because xylem embolism resistance appears a rather conservative trait (Fuchs et al. 2021), it remains speculative whether a given Douglas-fir provenance differs in xylem safety when planted in Central Europe. In Scots pine, for example, Martinez-Vilalta et al. (2009) did not observe any relationship between the $P_{50}$-value and climatic aridity across Europe despite covering a precipitation gradient of 371 mm yr$^{-1}$ and a range in vapor pressure deficit of 1.29 kPa. However, the leaf-to-sapwood area ratio, the reciprocal of the Huber value (HV; Huber, 1928), showed a close linear relationship with climatic dryness, i.e., the same xylem area supported less leaf area at drier sites in this coniferous tree species with a wide ecological amplitude (Martinez-Vilalta et al. 2009). For Douglas-fir, comparable data along an environmental gradient are not yet available, but Chauvin et al. (2019) measured xylem embolism resistance in two provenance trials from Southern France and Corsica. Between both trials, the $P_{50}$-value on average differed by 0.03 MPa only. We therefore speculate that Douglas-fir, like Scots pine, reduces its supported leaf area in response to climatic aridity instead of increasing xylem safety. In this context, we consider the Huber value, i.e., the sapwood-to-leaf area ratio ($A_{xylem}:A_{leaf}$), as an hydraulic efficiency trait (Tyree and Zimmermann 2002; Mencuccini et al. 2019).

Under prolonged drought exposure, stomata tend to close more frequently, which is mirrored in the carbon isotope signature (δ$^{13}$C) of leaf bulk dry mass (Diefendorf et al. 2010). The δ$^{13}$C-value further appears to be a good proxy for long-term intrinsic water use efficiency (iWUE) (Petrik
et al. 2023; Kurjak et al. 2024). Trees with a high iWUE have a low H₂O loss per CO₂ absorbed, and that ratio can be optimized either by reducing transpiration and/or by more efficient CO₂ uptake (Flexas et al. 2016; Hatfield and Dold 2019). Likewise, at the leaf level, the specific leaf area (SLA) has often been related to drought-adapted behavior and growth performance across and within species. A high SLA has been associated with high growth rates, as the leaf area for photosynthesis and gas-exchange is increased (Grace 1990). However, traits that enhance growth typically reduce stress tolerance (Guillemot et al. 2022).

For the transformation towards future climate-resilient forests, it is crucial to know whether certain Douglas-fir provenances are better suited for cultivation in Central Europe. Here, we focus on comparing six growth-related and drought tolerance traits at the leaf and xylem level of 28 Douglas-fir provenances from three different climatic origin groups that were planted between 1975 and 1980 on five sites situated along a climatic gradient. We speculate that (i) Douglas-fir provenances from three climate origins groups differ in growth and hydraulic traits, (ii) leaf traits show a larger variability between sites differing in climatic aridity than xylem traits, and (iii) climatic origin and environmental conditions at the growing site explain a significant fraction of the variance in growth as well as leaf and xylem traits.

# Materials and methods

## Study sites and climate

The five Douglas-fir provenance trials included in the present study were situated in Central Europe, spanning approximately 350 km from northwest to southeast Bavaria and along a rainfall gradient (Figure 1a). The sites at Bad Brückenau (BAD) and Hammelburg (HAM) were established by the Bavarian Office for Forest Genetics (AWG) in 1975 as part of an international seed collection program organized by the International Union of Forest Research Organizations (IUFRO). In the following years until 1980, three additional sites were added to further evaluate high-performing provenances under varying site conditions (Table 1).

The sites cover latitudes from 48.74° to 50.32° and longitudes from 9.62° to 13.10° (Figure 1a, Table 1). They were designed using a randomized block design with three blocks each with a block size of 10 m × 10 m and a plant spacing of 2 m × 2 m, resulting in a total of 2,700 plants from 36 provenances per site at planting time. For our study only 15 provenances per site are chosen according to the provenance grouping described in the next section.

Monthly climatic data from 1970 to 2022 were downloaded from the German Weather Service (Deutsche Wetterdienst, DWD 2022) open data server. The study

sites followed a gradient of temperature and precipitation, ranging from 6.7 ± 0.85 °C to 8.7 ± 1.01 °C and 793.38 ± 113.27 mm yr⁻¹ to 1334.96 ± 251.37 mm yr⁻¹, respectively (Table 1). We further estimated the climatic water balance (CWB), which is calculated by subtracting potential evapotranspiration (PET, calculated after Monteith 1965) from precipitation. As a result, we cover a CWB range of 690 mm yr⁻¹ across our gradient from +109 mm yr⁻¹ at the site near Freising (FRE) to +581 mm yr⁻¹ at the site near Bodenmais (BOD) (Table 1, Figure 1b).

## Provenance selection and clustering into climate-origin groups

The 28 studied provenances were not replicated evenly across the five sites because the trials established between 1975 and 1980 did not cover the same set of provenances (Table S1). Therefore, we decided to group the provenances into three climate-origin groups according to the climatic conditions at their place of origin (Figure 2). The groups were created based on a hierarchical clustering of the bioclimatic variables (WorldClim 2022) at the place of origin. Precise information about the chosen provenances, their spatial location, and averages of the measured values as well as the differences in climate origin are listed in the Supporting information (Table S1, Figures S1 and Figure S2).

We selected the most vital and dominant tree from each provenance at each site. To calculate aboveground biomass increment (ABI), AGB was divided by tree age, which was estimated from year of site establishment plus age of the saplings. Sapling age (3 years) was consistent across all sites except BOD; here the age of the planted saplings was five years.

## Tree structure and aboveground biomass increment

For every sampled tree, the diameter at breast height (DBH) was taken with a circumference tape measure and height (h) measured with a Vertex IV hypsometer with transponder T3 (Haglöf, Längesele, Sweden). The height and DBH were then used to estimate the tree biomass (AGB<sub>it</sub>, kg) based on the allometric equation by Thurm and Pretzsch (2016).

$$AGB_{it} = e^{-3.211} \cdot DBH^{2.008} \cdot h^{0.730}, \quad (1)$$

## Branch sampling

Sampling of upper-most and sun-exposed branches took place in the growing season of 2023 from May to August. We used a Big Shot throw-line launcher (SherrillTree Inc., Greensboro, NC, USA) for shooting a weight tied to a small rope over one branch (Table S2). Once hit, a hand chainsaw
<figure><img src="image_4.png" /><figcaption>**Figure 1** a Map of five selected provenance trial site locations in Central Europe. Dots represent the site location and the color increases from dry (orange) to moist (purple). b Annual mean climatic water balance ± standard deviation (CWB, 1970-2022), colored according from most negative (orange) to most moist (purple)</figcaption></figure>

<table><caption>**Table 1** Site and tree characteristics of the studied stands sorted by ascending order of the local climatic water balance (CWB)</caption><thead><tr><th>Site</th><th>Lat.</th><th>Lon.</th><th>m.a.s.l.</th><th>Plant year</th><th>MAP (mm)</th><th>MAT (°C)</th><th>CWB (mm)</th><th>Tree height (m)</th><th>DBH (cm)</th><th>n-samples</th></tr></thead><tbody><tr><td>FRE</td><td>48.735</td><td>11.804</td><td>430</td><td>1980</td><td>793.38±113.27</td><td>8.64±0.86</td><td>187.32±150.61</td><td>30.64±3.52</td><td>33.52±7.73</td><td>45</td></tr><tr><td>HAM</td><td>50.076</td><td>9.62</td><td>365</td><td>1975</td><td>883.98±171.95</td><td>8.7±1.01</td><td>270.74±205.99</td><td>39.20±4.78</td><td>42.3±6.17</td><td>39</td></tr><tr><td>NOR</td><td>50.181</td><td>11.511</td><td>510</td><td>1978</td><td>870±153</td><td>7.84±0.87</td><td>292.88±186.84</td><td>29.96±3.06</td><td>34.59±4.49</td><td>33</td></tr><tr><td>BAD</td><td>50.322</td><td>9.8</td><td>415</td><td>1975</td><td>1000.67±163.77</td><td>7.5±0.92</td><td>425.5±194.41</td><td>39.97±4.94</td><td>40.73±7.66</td><td>27</td></tr><tr><td>BOD</td><td>48.876</td><td>13.095</td><td>805</td><td>1980</td><td>1334.96±251.37</td><td>6.7±0.85</td><td>764.73±268.95</td><td>32.37±3.36</td><td>37.26±5.37</td><td>45</td></tr></tbody></table>

n-samples are the number of branches taken for measurements. MAP, MAT, CWB, Tree height, and DBH are given as means ± standard deviation

MAP mean annual precipitation (period 1970–2022), MAT mean annual temperature (period 1970–2022), CWB climatic water balance (period 1970–2022), DBH stem diameter at breast height

(RoNa Werkzeuge GmbH, Düsseldorf, Germany) was pulled up to saw off the branch. In total, three branches were harvested per tree, recut at the ground to an approximate length

of 150 cm, wrapped in well-wetted blankets and stored in black plastic bags for transportation to prevent the leaves from further transpiring.
<figure><img src="image_5.png" /><figcaption>**Figure 2** a Map of provenances in North America clustered into three climate-origin groups (C1 = green, C2 = beige, C3 = blue). b PCA of climate-related variability between Douglas fir provenances based on 19 bioclimatic indexes (supplementary Table S6). Red vectors are</figcaption></figure>

related to temperature (Bio 01–Bio 11) and blue represent precipitation related values (Bio 12–Bio 19). Three climate-origin groups (C1, C2, C3) are colored according to map in a

## Vulnerability curves

Vulnerability curves (VCs) for 189 branches were measured with the flow-centrifuge method using a Cavitron device (Cochard et al. 2005) built from a Sorval RC 5 Plus centrifuge with manual rotation speed control. Data were acquired and analyzed with the Cavisoft software (version 5.2.1, University of Bordeaux, Bordeaux, France). Before measurement, the distance from the sample end to the tip of the branch sample was recorded, branches were trimmed to a final length of 27.5 cm, lateral twigs were excised, and their bark completely removed to avoid occluding conduits with resin. Prior to insertion in the rotor, we measured branch diameter on six equally spaced positions along the length of the segment. Hydraulic conductance measurements started at a water potential of -0.8 MPa, which was gradually reduced until percent loss of conductivity (PLC) reached at least 90%. Vulnerability curves were built using a sigmoidal logistic model by Pammenter & Vander Willigen (1998) modified based on hydraulic conductivity (Ogle et al. 2009) as:

$$ \hat{K}_i = K_{\text{sat}} \cdot \left( 1 - \frac{1}{1 + \exp\left(-\frac{s_{50}}{25}(P_i - P_{50})\right)} \right), \quad (2) $$

where for each observation i, the expected conductivity $\hat{K}_i$ is expressed as a logistic function of the water potential $P_i$ with the parameters $P_{50}$ (water potential at 50% loss of conductivity), $S_{50}$ (slope on the PLC scale) and $K_{\text{sat}}$ (conductivity at full saturation). Other critical water potentials ($P_{12}$, $P_{88}$) were calculated by substituting and rearranging Eq. (2). According to a simple linear model, distance to tip (measurement from tip of branch to the upper part of Cavitron sample) was unrelated to the xylem pressure causing 50% loss of hydraulic conductance ($R^2 = 0.007$, $p = 0.27$, $n = 189$; data not shown).

## Leaf traits

From the VC samples, all leaves distal to the basipetal end until the tip were collected, placed in plastic bags, and stored
in a refrigerator at 4 °C for a maximum of four weeks until further processing. For each VC sample, subsamples of on average 334.7 ± 31.01 (mean ± SD) leaves were scanned (Epson GmbH, Expression 11000XL, Düsseldorf, Germany). Total leaf area of this subsample (A<sub>scan</sub>, cm²) was measured with ImageJ (v1.54d, Schneider et al. 2012). Subsequently, all leaves were oven-dried at 70 °C for 72 h. The dry mass (DM, g) of the subsamples were weighed using a precision balance (AC 120S, Sartorius GmbH, Göttingen, Germany) to calculate the specific leaf area (SLA, cm² g⁻¹). Additionally, the remaining leaves were weighted separately and in combination with the SLA of the subsample used to estimate the total leaf area of the VC sample as A<sub>leaf</sub> (cm²) = SLA (cm² g⁻¹) × DM (g). A<sub>leaf</sub> was used to estimate the Huber Value (HV, m² m⁻², unitless), i.e., the sapwood-to-leaf area ratio, by dividing the conductive xylem area of the basipetal end of the VC sample by the total supported leaf area of the sample. The xylem area was considered as the total cross-sectional area of the basipetal end including the pith but excluding the bark.

The carbon isotope signature (δ¹³C, ‰) of the leaf dry mass was analyzed by mass ratio spectroscopy (Deltaplus; ThermoFinnigan, Bremen, Germany) at the Centre for Stable Isotope Research and Analysis (KOSI), University of Göttingen.

## Statistical analysis

All statistical analysis was conducted with R v.4.2.3 (R Core Team, 2023). To assess the effect of water availability on intraspecific trait variation, sets of linear mixed-effects models were fitted with R package lme4 v. 1.1-35.4 (Bates et al. 2015). Each trait (AGB, SLA, HV, δ¹³C, P₅₀) (Table S4) was modelled with climate group and CWB as fixed effects (the latter centered and scaled to simplify the comparison of regression coefficients) and tree-wise random intercepts. Due to our unbalanced study design, random provenance effects could not be included as there were several singlets or doublets, which resulted in convergence issues and singular fits. The explained variance was calculated with R package MuMln v. 1.48.3 (Barton et al. 2023) according to Nakagawa and Schielzeth (2013).

To decompose the variance of each trait on different levels of organization (climate groups, plots (populations), between-tree and within-tree variation; see Table S5), mixed-effects models were fitted for each trait separately using lme4 (Bates et al. 2015). Each model contained fixed effects for climate group, as well as random tree and plot effects. The model for ABI did not contain tree effects as there is only one measurement for the biomass per tree. The total variance in the traits was decomposed into variance components for the fixed and random effects as well as the residual (within-tree) standard deviation, analogous to the

definition of conditional and marginal R² (cf. Nakagawa and Schielzeth 2013).

For all dependent variables, model residuals were checked for normality and natural log-transformed whenever required to meet the assumption of normality. Data on the branch level were averaged per tree, and this average was used for further statistical analysis. P values from linear mixed effects models were obtained by t-tests with Satterthwaite's approximation to the degrees of freedom based on R package lmerTest v. 3.1-3 (Kuznetsova et al. 2017).

Climatic groups were defined as in Riedel et al. (unpublished) using a hierarchical clustering of the PCA axes (base R function prcomp()) of the full dataset of the scaled and centered WorldClim bioclimatic variables (WorldClim 2022) based on the base R function hclust() (Langfelder & Horvath 2012). The first two principal components explain 93.5% of the variance in the climate data (Table S6). Vulnerability curves were fitted using nonlinear least squares with base R function nls() according to Eq. (2).

## Results

### Differences between climate-origin groups

Averaged across the five sites, aboveground biomass increment (ABI, kg yr⁻¹) was significantly lower for the northern interior climate-origin group (13.06 ± 7.11 kg yr⁻¹, C3) compared to the northern coastal (18.55 ± 4.43 kg yr⁻¹, C2) and southern coastal (18.42 ± 7.76 kg yr⁻¹, C1) groups (Table 2, Table S3, Figure 3a). Trees from the C3 climate-origin group being visibly smaller compared to coastal provenances. No significant differences in ABI were observed between the two coastal groups. For the Huber value (HV; mean range from 0.23 to 0.32), which we consider as a hydraulic efficiency trait, and leaf δ¹³C (mean range from −27.7 ‰ to −28.07 ‰) as proxies for long-term intrinsic water use efficiency (iWUE), no significant differences between climate-origin groups were detected (Table 2, Figure 3c, d). A similar pattern was observed for the two hydraulic safety-related traits P₁₂ (mean range from −2.92 MPa to −3.04 MPa) and P₅₀ (mean range from −3.47 MPa to −3.56 MPa) (Figure 3e, f), which did not differ significantly between the three climate-origin groups. However, the northern group (C3) did not only show the lowest growth rates, but also the lowest specific leaf area (SLA) (Figure 3b, Table S3).

### Variation in functional traits along the climatic gradient

Across the five sites of our CWB gradient, ABI differed significantly only within the northern interior climate-origin group (C3) (Figure 4a). These differences, however, did
<table><caption>**Table 2** Results of the linear mixed effects models examining the relationships between climatic water balance (CWB) and functional traits</caption><thead><tr><th>Climat-origin gr.</th><th>Term</th><th>ABI</th><th>SLA</th><th>HV</th><th>δ<sup>13</sup>C</th><th>P<sub>50</sub></th></tr></thead><tbody><tr><td rowspan="5">C1 - coast S</td><td>CWB</td><td>-0.043</td><td>-0.016</td><td>-0.044</td><td>0.007</td><td>-0.021</td></tr><tr><td>Tree SD</td><td>0.327</td><td>0.094</td><td>0.642</td><td>0.051</td><td>0.042</td></tr><tr><td>Res. SD</td><td>0.340</td><td>0.078</td><td>0.429</td><td>0.024</td><td>0.059</td></tr><tr><td>Marg. R<sup>2</sup></td><td>0.008</td><td>0.017</td><td>0.004</td><td>0.017</td><td>0.082</td></tr><tr><td>Cond. R<sup>2</sup></td><td>0.486</td><td>0.597</td><td>0.692</td><td>0.831</td><td>0.394</td></tr><tr><td rowspan="5">C2 - coast N</td><td>CWB</td><td>0.071</td><td>-0.009</td><td>0.004</td><td>0.017</td><td>-0.010</td></tr><tr><td>Tree SD</td><td>0.220</td><td>0.094</td><td>0.155</td><td>0.039</td><td>0.043</td></tr><tr><td>Res. SD</td><td>0.164</td><td>0.059</td><td>0.482</td><td>0.019</td><td>0.061</td></tr><tr><td>Marg. R<sup>2</sup></td><td>0.063</td><td>0.006</td><td>0.000</td><td>0.142</td><td>0.019</td></tr><tr><td>Cond. R<sup>2</sup></td><td>0.665</td><td>0.724</td><td>0.093</td><td>0.835</td><td>0.339</td></tr><tr><td rowspan="5">C3 - interior N</td><td>CWB</td><td>0.021</td><td>-0.013</td><td>0.091</td><td>0.002</td><td>0.008</td></tr><tr><td>Tree SD</td><td>0.197</td><td>0.109</td><td>0.000</td><td>0.038</td><td>0.048</td></tr><tr><td>Res. SD</td><td>0.406</td><td>0.092</td><td>0.457</td><td>0.027</td><td>0.056</td></tr><tr><td>Marg. R<sup>2</sup></td><td>0.002</td><td>0.008</td><td>0.040</td><td>0.001</td><td>0.012</td></tr><tr><td>Cond. R<sup>2</sup></td><td>0.192</td><td>0.587</td><td>0.040</td><td>0.665</td><td>0.429</td></tr></tbody></table>

Given are the scaled estimates for CWB (climatic water balance), the standard deviation for the tree-wise random intercept (Tree SD), the residual standard deviation (Res. SD), and marginal and conditional R² of the models (Marg. R² and Cond. R²). The full output of the models is given in Table S3)

ABI aboveground biomass increment, SLA specific leaf area; Huber value (HV) A<sub>xylem</sub>/A<sub>leaf</sub> — ratio of branches, δ<sup>13</sup>C carbon stable isotope ration of leaves, P<sub>50</sub> xylem water potential at 50% loss of conductivity

not reflect the CWB gradient, as the driest site (FRE) and the moistest site (BOD) had comparable growth rates. For SLA, no significant differences were observed between sites within a climate-origin group (Figure 4b). Although non-significant, it is striking that the driest site (FRE) always had the highest mean values for each climate-origin group (mean SLA on FRE: C1 = 81.62 ± 6.65; C2 = 74.15 ± 10.11; C3 = 70.65 ± 11.27 cm² g⁻¹).

The Huber value (HV) was not influenced by the climatic gradient (Figure 4c). Only within the climate-origin group C1, at the site BAD, the mean was significantly different (Figure 4c; mean HV for C1 = 0.86 ± 0.7). In contrast, δ<sup>13</sup>C values showed the greatest variability both within and between sites for each climate-origin group, but no clear pattern was observed (Figure 4d). Although no relationship between climatic gradient and δ<sup>13</sup>C was observed, it is remarkable that the pattern itself is similar for each climate-origin group. Arranging climate-origin group by increasing δ<sup>13</sup>C values results in the following order: BAD > BOD > FRE > HAM > NOR, with the most negative values at site BAD (C1 = -29.23 ± 0.52 ‰; C2 = -29.12 ± 0.67 ‰; C3 = -28.34 ± 0.45 ‰) and the least negative at site NOR (C1 = -26.69 ± 1.07 ‰; C2 = -26.59 ± 0.88 ‰; C3 = -26.85 ± 1.4).

The two hydraulic safety traits P<sub>12</sub> and P<sub>50</sub> appeared to be the most conservative traits of our sample, as no significant

differences across the climatic gradient were found within a climate-origin group (Figure 4e, f). Across the three climate-origin groups, P<sub>12</sub> ranged from -1.52 to -3.38 MPa and P<sub>50</sub> from -3.01 to -3.83 MPa.

Our observation that the CWB has no significant influence on the traits captured by this study is supported by a low marginal R² (ranging from 0.04 to 0.142, Table 2), showing that only a small fraction of variance is explained by CWB. The substantially higher conditional R² values (ranging from 0.04 to 0.835, Table 2) indicate that most of the variance was not accounted for by CWB. Instead, it can be primarily attributed to unexplained differences between sites and individual variability.

## Intra-specific trait variability on different levels of organization

For all five growth-related, leaf morphological and hydraulic traits covered—namely ABI, SLA, HV, δ<sup>13</sup>C, and P<sub>50</sub>— the within-population variability (including both intra- and inter-individual differences) exceeded the variability observed between populations (Figure 5). In contrast to P<sub>50</sub>, efficiency-related traits (HV and δ<sup>13</sup>C) almost exhibited no differences between climate-origin groups, but varied substantially between and within individual trees (Figure 5). For growth related traits ABI (21%) and SLA (18%), a substantial amount of variance could be explained by our grouping by climate at origin (climate group).

## Discussion

### Trait variability between climate-origin groups

Our experimental approach of clustering Douglas-fir provenances by bioclimatic variables into three climate-at-origin groups revealed significant differences in aboveground biomass increment (ABI) of mature trees cultivated in Central Europe between these groups, indicating that the growth potential of that species is at least partially determined by the climatic conditions at their place of origin. The northern interior provenances (C3) on average had a 5.4 kg yr⁻¹ lower aboveground biomass increment than the two coastal climate-at-origin groups (C1, C2). Supporting our results, Sergent et al. (2014) likewise observed that 30-year-old coastal Douglas-fir provenances performed better than interior provenances in a comparable provenance trial in France. Similar results have been reported from Germany (Konnert et al. 2008; Konnert and Bastein 2019), supported by field-grown data from Northern America (Rehfeldt et al. 2006). According to our climate origin clustering of the provenances, the northern interior group (C3) originates from a climate that is characterized by strong temperature
<figure><img src="image_6.png" /><figcaption>**Figure 3** Boxplots for measured traits for each climate-origin group (C1 = green, C2 = beige, C3 = blue) a Growth rate as aboveground biomass increment (ABI), b specific leaf area (SLA), c Ratio of xylem area to SLA (Huber value, HV), d Carbon stable isotope ratio of leaves (δ¹³C), e Xylem water potential at 12% loss of conductivity (P₁₂), f Xylem water potential at 50% loss of conductivity (P₅₀).</figcaption></figure>

Box-whisker plots include median and interquartile ranges (Q1-Q3); whiskers extend to maximum 1.5 times the interquartile range. Different letters denote significantly different means based on Tukey-adjusted p-values from linear mixed effects models with post hoc tests for pairwise species differences with degrees of freedom based on Satterthwaite's approximation

differences throughout the year (Figure 2, Figure S1, S2). The climate at the southern coastal origin group (C1) differs from that of the northern coastal (C2) by approximately 5 °C in mean annual temperature and 1000 mm yr⁻¹ in mean annual precipitation (Figure 2, Figure S1, S2).

No significant differences between the three climate-origin groups were observed for the hydraulic traits estimated in the present study. Neither the supported leaf area per xylem cross-sectional area, xylem safety nor long-term intrinsic water use efficiency differed between the three groups. Despite the observed differences in growth between

the coastal and interior provenances, the hydraulic system of Douglas-fir does not appear to be related to the climate of origin. For xylem safety, we indeed expected limited variability, as this trait seems to be rather conservative and evolutionarily canalized at the intra-specific level in gymnosperms (Saenz-Romeri et al. 2013; Lamy et al. 2014; David-Schwartz et al. 2016; Chauvin et al. 2019).

Instead, the specific leaf area (SLA) was lower for interior (C3) than coastal provenances (C1, C2). The interior provenances not only showed a lower growth performance, but also had smaller and thicker needles. According to the
leaf economic spectrum (Wright et al. 2004; Poorter et al. 2014), a high SLA is associated with acquisitive strategies that prioritize fast growth over longevity and structural stability. In larger and thinner leaves with a high photosynthetic area, transpiration is enhanced, which increases the mobilization of nutrients and CO₂ uptake (Grace 1990; Marks & Lechowicz 2007).

This implies that coastal provenances to a certain degree might be more vulnerable to drought stress. However, our study provides mixed evidence in this regard as the groups were rather similar in hydraulic traits, with neither a difference in xylem safety nor the supported leaf area. It therefore remains questionable whether higher growth rates associated with larger and thinner needles trade-off with drought tolerance in Douglas-fir. Other known hydraulic traits at play during the two phases of drought response of trees, like the water potential at 90% stomata closure (Pgs90), capacitance (C), minimum conductance (gmin), or hydraulic safety margins (HSM) (cf., Waite et al. 2024), could reveal differences between our climate-origin groups.

## Effects water availability along the gradient on trait variability

Across our five sites, we did not observe any clear patterns in the studied traits along covered gradient in water availability estimated by the climatic water balance (CWB) – for any of the studied climate groups. For xylem safety, this outcome was expected, as comparable studies along environmental gradients did not observe an effect of climatic variability on embolism resistance in conifers (Martinez-Vilalta et al. 2009; Lamy et al. 2014; Sáenz-Romero et al. 2013; Gonzales-Munoz et al. 2018; Chauvin et al. 2019). However, we expected a clear signal for the Huber value, as reported by Martinez-Vilalta et al. (2009) for Scots pine (*Pinus sylvestris*), and additionally for Black pine (*Pinus nigra*) and Aleppo pine (*Pinus halepensis*) by Rosas et al. (2019). Several reasons might be responsible for the absence of plasticity along our gradient. First, although we covered a precipitation reduction by 542 mm yr⁻¹, all sites are characterized by a high precipitation regime with at least 401 mm during the growing season from April to September. Second, we did not include any measurements of edaphic aridity, which in Central Europe might be more influential for a trees’ hydraulic status than climatic aridity (cf., Fuchs et al. 2021; Weithmann et al. 2022). And lastly, the Huber value is known to be highly variable both within and across trees, and might differ by up to an order of magnitude within a given species (cf., McDowell et al. 2002; Pritzkow et al. 2020; Fuchs et al. 2021; Ramesha et al. 2022).

For SLA and ABI, the climatic conditions at the sites across our gradient did not influence these traits despite observed differences between climate-origin groups. It

therefore seems reasonable to attribute the observed differences between the coastal and northern interior provenances to the prevailing climatic conditions at their places of origin.

The most variable of our measured traits was the carbon isotope signature (δ¹³C) of the leaves, which is considered a proxy for the long-term intrinsic water use efficiency (iWUE) (Petrik et al. 2023). However, also in this case the variability could not be attributed to differences in climatic conditions along our gradient, though the patterns within the climate-origin groups were similar. As the ordering of δ¹³C was unrelated to CWB, we speculate that either soil properties related to soil water holding capacity and/or tree height might be responsible. It is well documented that δ¹³C becomes less negative with height in the canopy due to increasing hydraulic constraints (e.g., Buchmann et al. 1997; Sala and Hoch 2009; Schuldt et al. 2011). A comparably high variation in δ¹³C as in our study (average range in δ¹³C: -26.59 to -29.37 ‰; Fig. 5) has been observed by Panek & Waring (1995) for Douglas-fir across a climatic gradient in Oregon. These authors attributed their findings to differences in branch length and the climatic conditions at the place of growth. However, our findings highlight a remarkable intra-specific variability in iWUE among Douglas-fir provenances (Δδ¹³C: 3.85 ‰; Table S1), highlighting its potential for breeding programs. Based on this trait only, the populations at NOR would be the best population for a drought adapted future forest, as these trees have the least negative δ¹³C and therefore highest iWUE (cf., Petrik et al. 2024).

## Sources of variation on different levels of organization

Our study on mature Douglas-fir trees revealed a surprisingly low variability in embolism resistance (as quantified by the *P*<sub>50</sub>-value) along an environmental gradient in Central Europe and across the three climate-origin groups. Within a climate-origin group, *P*<sub>50</sub> varied by 0.2–0.4 MPa across the gradient while the three climate-origin groups differed by 0.1 MPa only. Our results thus support observations by various authors that embolism resistance is an evolutionarily canalized trait in conifers (Saenz-Romeri et al. 2013; Lamy et al. 2014; David-Schwartz et al. 2016; Chauvin et al. 2019; Sanchez-Martinez (2020); Laughlin et al. 2020). While some older studies using the air-injection method report *P*<sub>50</sub>-values around −5 MPa or lower for Douglas-fir branches (Sperry & Ikeda 1997; Kavanagh et al. 1999; Stout & Sala 2003; Domec et al. 2006), our results obtained by the flow-centrifuge technique (average *P*<sub>50</sub> ± SD across provenances: −3.50 ± 0.03 MPa; Tab. S1) are in a similar range as recently reported for mature trees (−3.38 MPa; Schumann et al. 2024) and saplings (−4.09 MPa; Paligi et al. 2024) in Central Europe. In southern France, Chauvin et al. (2019) report even less negative values (−3.19 MPa) across
<figure><img src="image_7.png" /></figure>

<figure><img src="image_8.png" /></figure>

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

Climatic water balance (mm yr.⁻¹)

<figure><img src="image_13.png" /></figure>
◄**Figure 4** Growth and specific leaf area: a Growth rate as above-ground biomass increment (ABI) and b specific leaf area (SLA) of the three climate-origin groups at all study sites. Hydraulic traits: c Ratio of xylem area to leaf area (Huber value, HV), d Carbon stable isotope ration of leaves (δ¹³C), e Xylem water potential at 12% loss of conductivity (P₁₂), and f Xylem water potential at 50% loss of conductivity (P₅₀) of the three climate-origin groups at all study sites. Sites are sorted in ascending order according to the climatic water balance. Different letters denote significantly different means between sites within a species based on Tukey-adjusted p-values with degrees of freedom based on Satterthwaite's approximation from linear mixed effects models with post hoc tests for pairwise differences

10 provenances at two sites. As the field of plant hydraulics has faced quite some controversies in the past, we speculate that the air-injection method, which is known to be prone to measurement artefacts in angiosperms (Ennajeh et al. 2011), might produce more negative values compared to the flow-centrifuge technique in conifers as the positive air pressure has to penetrate through the bark in order to enter the xylem, which deserves further testing. However, the intra-specific trait variability in P₅₀ appears limited in Douglas-fir, at least in Central Europe, which might explain the absence of any climatic imprint. In European beech (Fagus sylvatica), however, Schuldt et al. (2016) observed a close linear relationship between mean annual precipitation (MAP) and embolism resistance although P₅₀ only varied by 0.3 MPa across the gradient. Despite their observed effect of climatic aridity on P₅₀, Schuldt et al. (2016) observed the highest fraction of intra-specific trait variability within given trees, and the lowest between sites. In our study on Douglas-fir, within-tree variability likewise contributed a large fraction of the total variance in P₅₀ (63%), while only a minor part could be attributed to the climate-origin groups (3%). The between-tree variability additionally includes effects of other unexplained factors, for example soil properties, insect pests, or growth-related competition effects. All these factors increased the explained variance in a comparable study on intraspecific variability of species along a climatic gradient by Albert et al. (2010). Although we collected all branches from similar canopy height positions and orientation, the inner-tree variation is surprisingly high, not only in P₅₀ but also in the Huber value (HV). According to Coleman et al. (1994), this could partly be attributed to ontogenetic effects as genotypically similar trees can have different stages of development at the same age in different environments. In our study, however, all trees are of comparable age, though branch age might differ. At least in European beech, branch age was found to vary considerably in branch segments of similar diameter from the uppermost canopy (Weithmann et al. 2022b). This could partly explain the large within-tree variability, since we did not control for the effects of branch age.

The variance explained by a general between-tree variability is most likely explained by genetic or environmental

effects that could not be covered by our study, for example within provenance genetic differences or within-stand small-scale environmental differences that are generally hard to capture (cf., Albert et al. 2010; Laforest-Lapointe et al. 2014). In European beech, for example, Weithmann et al. (2022a) did only observe an effect of edaphic aridity on P₅₀ but not climatic aridity.

Finally for leaf related traits (SLA and δ¹³C) the within-tree effects are rather low. The between tree effect is with 41.46% for the SLA and 47.7% for δ¹³C the most important effect. A substantial amount of the variance in δ¹³C (29.24%) is explained by the plot. That aligns with the consistent patterns observed for δ¹³C across the gradient as mentioned above and indicates that other abiotic drivers—such as the soil water holding capacity—not covered by our study might be more influential than climatic aridity. For the SLA the climate origin has the second highest effect size with 18.81%. This lets us speculate that this trait seems to be related to a climate at origin.

## Conclusion

Douglas-fir is a promising tree species for future-proofing the production forests in Central Europe. The large natural geographical distribution of this coniferous species in Northern America is indicative for a high adaptive potential, which might differ between provenances. Our study on 28 Douglas-fir provenances from three climate-origin groups revealed a high intra-specific trait variability in above-ground biomass increment and specific leaf area between northern interior and coastal provenances when grown in Central Europe. Most likely, this finding can be attributed to genotypic variability. While the coastal provenances showed higher growth performance, branch xylem embolism resistance did not differ from the northern-interior provenances. It seems advisable to maintain the favorized cultivation of coastal provenances in Central Europe. However, we recommend to further evaluate whether the observed lower specific leaf area of the northern-interior provenances might be attributed to a higher drought tolerance despite that xylem safety was comparable. Across our precipitation gradient of 542 mm yr⁻¹, however, no effect of climatic aridity on any of the traits covered was observed. For xylem safety, a trait which is known to be rather conservative and evolutionarily canalized in conifers, this finding was expected. We were surprised, however, that Douglas-fir did not have a lower supported leaf area per cross-sectional xylem area in more arid sites as previously observed in Scots pine. Either our sites were all too moist and water availability was not limiting, or we did not cover other, more influential abiotic factors. If possible, future studies should therefore additionally cover soil physical properties.
<figure><img src="image_14.png" /><figcaption>**Figure 5** Variance decomposition between different levels of organization (between climate groups, between provenances, between and within individuals; see Supporting Information Table S4 for full model output) based on linear mixed effects models. Given are the aboveground biomass increment (ABI), specific leaf area (SLA), Ratio of xylem area to leaf area (Huber value, HV), Carbon stable isotope ratio of leaves (δ¹³C), and the xylem water potential at 50% loss of conductivity (P₅₀).</figcaption></figure>

While our approach of grouping provenances by climate origin with bioclimatic variables was a consequence of our study design, the observed differences between northern interior and coastal provenances align well with the literature. Therefore, we recommend to use this approach for grouping provenances in future studies in case the same provenances are not replicated across all sites, as it was the case in our study.

**Authors contributions** BS designed the study, VPR, PAW and RML developed and performed the provenance grouping. PE and VPR performed the field work and collected the samples, while PE did all the lab measurements. VPR analyzed and visualized the data and wrote the first manuscript, which was intensively discussed and revised by all authors.

**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s00468-025-02605-1.

**Acknowledgements** The authors gratefully acknowledge the financial support granted by the 'Bundesministerium für Ernährung und Landwirtschaft', 'Bundesministerium für Umwelt, Naturschutz und Nukleare Sicherheit' and the 'Fachagentur Nachwachsende Rohstoffe e.V.' within the frame of the 'Waldklimafonds' (project NONNATIVE; Fkz.: 2219WK08X4). We are thankful to Fon Robinson Tezeh for training PE in the use of the Cavitron.

**Funding** Open Access funding enabled and organized by Projekt DEAL. This work was supported by Fachagentur Nachwachsende Rohstoffe, 2219WK08X4, Bernhard Schuldt.

**Data availability** The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

## Declarations

**Conflict of interest** The authors have no relevant financial or non-financial interests to disclose.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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