Abstract
Information about the resistance and adaptive potential of tree species and provenances is needed to select suitable planting material in times of rapidly changing climate conditions. In this study, we evaluate growth responses to climatic fluctuations and extreme events for 12 provenances of northern red oak (Quercus rubra L.) that were tested across three trial sites with distinct environmental conditions in Germany. Six provenances each were sourced from the natural distribution in North America and from introduced stands in Germany. We collected increment cores of 16 trees per provenance and site. Dendroecological methods were used to compare provenance performance and establish climate-growth relationships to identify the main growth limiting factors. To evaluate the provenance response to extreme drought and frost events, three site-specific drought years were selected according to the Standardized Precipitation Evapotranspiration Index (SPEI) and 2010 as a year with an extreme late frost event. Resistance indices for these years were calculated and assessed in relation to overall growth performance. We observed a high variation in growth and in the climate sensitivity between sites depending on the prevailing climatic conditions, as well as a high intra-specific variation. Overall, summer drought and low temperatures in the early growing season appear to constrain the growth of red oak. The resistance of provenances within sites and extreme years showed considerable rank changes and interaction effects. We did not find a trade-off between growth and resistance to late frost, namely, fast growing provenances had a high frost hardiness. Further, there was no evidence for a trade-off between growth and drought hardiness. Still, responses to drought or late frost differ between provenances, pointing to dissimilar adaptive strategies. Provenances from introduced (i.e. German) stands represent suitable seed sources, as they combine a higher growth and frost hardiness compared to their North American counterparts. Drought hardiness was slightly higher in the slow-growing provenances. The results provide a better understanding of the variable adaptive strategies between provenances and help to select suitable planting material for adaptive forest management.
1 Introduction
The longevity and sessile nature of trees exposes them to diverse climate conditions during their lifetime. Due to climate change, these conditions nowadays not only include the climate variability typical for a specific region but also long- and short-term changes in climate, such as gradual increases in temperature and altered precipitation regimes that may lead to lower water availability in the growing season (). In particular, the frequency and severity of extreme events is increasing, which challenges tree populations to cope with harsh conditions, resulting in reduced productivity, crown defoliation or even mortality (; ). Trees are forced to rapidly adapt to the new conditions or migrate to more advantageous environments ().
Therefore, knowledge about the tolerance of tree populations to changing climate regimes is essential. Here, dendroecological studies focusing on climate responses of tree species relevant for forest management (; ) are deemed particularly important. Namely, such studies, which use tree rings to analyze the impact of ecological influences such as drought or late frost events on tree growth (), provide insights into climate-growth relationships and the resilience of trees to climate extremes at wide spatial and temporal scales (; ). Dendroecological studies may not only make an important contribution towards quantifying climatic tolerances of tree species but also of provenances. Hence, tree-ring based studies in provenance trials, established to compare the performance of multiple provenances of a species under different climatic and environmental conditions (), offer a great potential to explore intra-specific variation patterns and to define promising adapted provenances and thus suitable planting material for forest management ().
Tree-ring studies in Europe so far mostly focused on native tree species, e.g., with studies on Norway spruce (), Scots pine (), European larch (), European beech () and native oaks (). As a possible decline in growth and a loss of vigor of these native tree species due to rapid climate change poses serious problems for the resilience of forest ecosystems (), the focus has more recently widened to alternative species. These alternative tree species include introduced (non-native) species and could make an important contribution towards creating more resilient and climate-adapted forests in the future (; ). Northern red oak (Quercus rubra L.), hereafter named red oak, is one of those alternative species, promising due to its high growth potential, versatile use of wood and presumably high climate tolerance (; ). The species is native to North America, though was introduced to Europe already over 300 years ago. Nowadays, red oak covers 350,000 ha in European forests and is the most widespread introduced deciduous species in Germany (55,000 ha) (; ). In its natural distribution, red oak covers a broad climatic and altitudinal gradient ranging up to 1,680 m a.s.l (; ). The precipitation regime varies between 760 and 2,080 mm and the mean annual temperature reaches 4°C in the northern and 16°C in the most southern part (). In Europe, and particularly in Germany, red oak grows across a large temperature gradient similar to that of its natural distribution, but it often experiences less precipitation (minimum 500 mm) (; ). Compared to native oaks (Quercus robur L. and Q. petraea (Matt.) Liebl.), it is suggested to have a higher tolerance to environmental stress and to be less affected by water deficits due to lower water consumption and a higher stomatal density (; ). Supposedly, red oak is tolerant to winter and spring frosts due to a later bud break, whereas it appears to be highly sensitive to autumn frosts ().
Despite the climatic potential of red oak, only few studies have addressed its climatic response and tolerance to extreme weather events, and thereby found contrasting results. A study conducted in the northern natural distribution, for example, revealed similar climatic responses of ring width and vessel characteristics () with the strongest effect of drought in the early growing season (), whereas a study conducted in the introduced range (Latvia) showed that water deficit in late summer was the most influential factor (). These contrasting findings illustrate that growth responses of red oak to climate fluctuations and extremes, such as drought and late frost, are not well understood. Overall, more knowledge about the adaptive potential of red oak, especially in its introduced range, is needed at the species and provenance level.
To elucidate the climate sensitivity of red oak in Central Europe, we perform dendroecological analyses on three sites of a provenance trial in Germany that are characterized by distinct environmental conditions and contain red oak provenances from the natural distribution as well as from introduced stands in Germany. A previous forest mensuration study at these sites revealed that the German red oak provenances outperformed those from the natural distribution, especially in environments with higher water availability (). This result poses the question whether a trade-off exists between growth and resistance to extreme drought and/or late frost events with German provenances following a ‘high risk, high gain’-strategy: We hypothesize that the higher growth of introduced provenances is coupled with a lower resistance to extreme conditions as compared to their North American counterparts. To explore this strategy, we sampled increment cores to (1) establish climate-growth relationships and identify differences in climate responses between provenances and sites. Further, we (2) examine the growth response to drought and late frost events using resistance indices. These were compared with the absolute growth performance to answer the question whether trade-offs exist. Based on the knowledge gained about differences in adaptive strategies between provenances, we (3) identify suitable provenances for the future.
2 Material and methods
2.1 Study design
We investigated growth responses of red oak using a provenance trial that was established by the Thünen Institute of Forest Genetics in 1991. Both provenances from the natural distribution as well as from introduced stands from Germany were planted on four sites, from which one site was abandoned due to a high mortality caused by rodents. The three remaining sites are located in northern (Dunkelsdorf, DDF), eastern (Waldsieversdorf, WSD) and central (Waechtersbach, WBH) Germany (Figure 1). All sites were set up as a randomized complete block design with four replications; for a detailed overview see . Climatically, the sites can be described as humid (Waechtersbach, Dunkelsdorf) and continental (Waldsieversdorf). Overall, the sites cover a precipitation gradient ranging from 862 mm in Waechtersbach to 586 mm in Waldsieversdorf (Table 1). The mean of the maximum temperature of the warmest and coldest month ranges from 21.8°C (Dunkelsdorf) to 23.6°C (Waldsieversdorf) and from -0.6°C to -1.7°C respectively (Supplementary Figure 1). The sediment material of the soil varies between silt in Waechtersbach, sandy loam in Dunkelsdorf and sand with clay bands in Waldsieversdorf.
Figure 1
Table 1
| Site | Latitude | Longitude | Altitude (a.s.l.) | MAT [°C] | MAP [mm] | SHM [C°/µm] | N trees |
|---|---|---|---|---|---|---|---|
| WBH | 50.27° N | 09.15° E | 330 | 9.3 | 862 | 47 | 190 |
| DDF | 53.97° N | 10.60° E | 50 | 9.2 | 758 | 53 | 191 |
| WSD | 52.54° N | 14.03° E | 80 | 9.7 | 586 | 67 | 192 |
Overview of sites, mean annual temperature (MAT), mean annual precipitation (MAP), summer heat:moisture index (SHM) and number of measured trees per site (N trees) (WBH, Waechtersbach; DDF, Dunkelsdorf; WSD, Waldsieversdorf).
2.2 Tree-ring data
In spring 2022, we collected increment cores of 16 dominant or co-dominant trees per provenance and site (i.e., four individuals per replicate). The 12 provenances sampled (Figure 1; Supplementary Table 1), originate from introduced stands in Germany as well as from stands in the natural distribution and were selected according to their occurrence on each site (
Tree-ring series of individual trees, obtained after averaging the measurements of the two cores per tree, were treated in two different ways. For studying the climate sensitivity of tree growth (cf. Section 2.4), individual series were detrended using a cubic-smoothing spline with a 50% frequency cut-off at 15 years. This procedure removes age and dimension-related trends and accentuates the high-frequent climate signal (
In order to assess and validate the quality of our chronologies, chronology statistics were calculated (Table 2). The standard deviation indicates the data dispersion around the mean and first-order autocorrelation represents the impact of growth from the previous to the current year (
Table 2
| P2 | P7 | P9 | P10 | P18 | P21 | P33 | P34 | P37 | P38 | P40 | P44 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Waechtersbach | ||||||||||||
| SD | 0.176 | 0.169 | 0.159 | 0.174 | 0.187 | 0.150 | 0.132 | 0.142 | 0.142 | 0.161 | 0.141 | 0.145 |
| AR1 | -0.102 | -0.212 | -0.204 | -0.024 | -0.114 | -0.137 | -0.197 | -0.144 | -0.212 | -0.105 | -0.095 | -0.144 |
| GLK | 0.785 | 0.783 | 0.753 | 0.750 | 0.765 | 0.754 | 0.797 | 0.809 | 0.769 | 0.752 | 0.808 | 0.763 |
| RBAR | 0.622 | 0.546 | 0.500 | 0.475 | 0.585 | 0.571 | 0.592 | 0.605 | 0.589 | 0.543 | 0.540 | 0.632 |
| EPS | 0.958 | 0.948 | 0.933 | 0.927 | 0.948 | 0.952 | 0.959 | 0.961 | 0.956 | 0.943 | 0.949 | 0.957 |
| Dunkelsdorf | ||||||||||||
| SD | 0.149 | 0.160 | 0.167 | 0.177 | 0.185 | 0.160 | 0.133 | 0.128 | 0.147 | 0.131 | 0.142 | 0.132 |
| AR1 | 0.075 | 0.121 | 0.121 | 0.035 | 0.060 | 0.087 | 0.027 | 0.048 | 0.108 | 0.082 | 0.098 | 0.057 |
| GLK | 0.741 | 0.771 | 0.699 | 0.722 | 0.647 | 0.718 | 0.729 | 0.740 | 0.690 | 0.715 | 0.714 | 0.736 |
| RBAR | 0.511 | 0.533 | 0.433 | 0.500 | 0.471 | 0.429 | 0.528 | 0.477 | 0.395 | 0.461 | 0.478 | 0.529 |
| EPS | 0.926 | 0.945 | 0.901 | 0.929 | 0.899 | 0.882 | 0.931 | 0.916 | 0.887 | 0.917 | 0.917 | 0.936 |
| Waldsieversdorf | ||||||||||||
| SD | 0.227 | 0.179 | 0.168 | 0.206 | 0.234 | 0.181 | 0.200 | 0.180 | 0.178 | 0.202 | 0.185 | 0.188 |
| AR1 | -0.352 | -0.203 | -0.204 | -0.225 | -0.319 | -0.192 | -0.306 | -0.258 | -0.364 | -0.333 | -0.380 | -0.381 |
| GLK | 0.843 | 0.740 | 0.738 | 0.787 | 0.883 | 0.711 | 0.818 | 0.746 | 0.805 | 0.767 | 0.813 | 0.836 |
| RBAR | 0.669 | 0.495 | 0.486 | 0.597 | 0.682 | 0.481 | 0.529 | 0.502 | 0.638 | 0.585 | 0.639 | 0.679 |
| EPS | 0.963 | 0.927 | 0.925 | 0.947 | 0.968 | 0.911 | 0.931 | 0.934 | 0.961 | 0.948 | 0.958 | 0.962 |
Chronology statistics for the common overlap period from 1999 to 2021 based on detrended provenance chronologies per site: standard deviation (SD), first-order autocorrelation (AR1), Gleichläufigkeit (GLK), series intercorrelation (RBAR) and expressed population signal (EPS).
2.3 Climate data
Climate data of each site were extracted as monthly means of maximum, mean and minimum daily temperature and monthly precipitation from a 1 × 1 km gridded database provided by the German Weather Service (
2.4 Data analysis
The climate sensitivity of tree growth was studied by establishing climate-growth relationships as bootstrapped correlation coefficients between the site- and provenance-specific chronologies and monthly climate variables (temperature, precipitation and SPEI). Correlations were calculated over a 16-month window from previous year June to current year September using the R package treeclim (
Besides analyzing long-term relationships between climate and tree growth, we compared growth resistance of red oak to extreme drought and late frost events. Following a classification after
Table 3
| Site | Drought years | Late frost event | T min May [°C] (mean 1991-2021) | |||
|---|---|---|---|---|---|---|
| Severe | max. SPEI (month) | Extreme | max. SPEI (month) | |||
| WBH | 2011 | -1.66 (May) | 2015 | -2.09 (July) | 2010 | 6.1 (7.9) |
| 2014 | -1.73 (June) | |||||
| DDF | 2003 | -1.79 (July) | 2018 | -2.19 (July) | 2010 | 5.7 (7.2) |
| 2009 | -1.80 (May) | |||||
| WSD | 2003 | -1.92 (May) | 2016 | -2.00 (May) | 2010 | 6.8 (7.9) |
| 2018 | -2.00 (June) | |||||
Analyzed extreme years per site.
Drought years are separated into severe (SPEI: -2.0 to -1.5) and extreme (SPEI < -2.0) drought events during the month May to July. 2010 was selected as a year with an extreme late frost event at all sites (WBH, Waechtersbach; DDF, Dunkelsdorf; WSD, Waldsieversdorf).
3 Results
3.1 Differences in spatial-temporal growth variation
The chronology characteristics displayed distinct differences in spatial-temporal growth variation between provenances and sites (Table 2). Standard deviation was highest in Waldsieversdorf followed by Waechtersbach and Dunkelsdorf, which points to variation in the common response of provenances to short-term climate changes. The autocorrelation of the provenance chronologies is generally low with a maximum of 0.12 (P7 and P9) in Dunkelsdorf, which had the highest values of the three sites. In Waechtersbach and Waldsieversdorf, autocorrelation is negative, displaying low carry-over effects from previous years’ growth. In general, Gleichläufigkeit and RBAR values were high, indicating a strong common growth signal of provenances within sites. Waldsieversdorf had the highest RBAR values (i.e. provenances from Germany and United States), showing a strong common response to climatic variation and the most coherent growth pattern. Likewise, all EPS scores exceeded the common applied threshold of 0.85, representing an adequate and common signal of the provenance chronologies.
3.2 Climate-growth relationships
Climate-growth relationships revealed distinct differences between sites and provenances (Figure 2). We found a significant positive correlation between growth and SPEI as well as negative correlations with mean and maximum temperature in June/July (Figure 2; Supplementary Figure 4). Furthermore, June precipitation was positively correlated at all three sites with increasing (significant) dependencies along the precipitation gradient from wet (Waechtersbach) to dry (Waldsieversdorf), identifying summer drought as one of the main climatic factors controlling tree growth of red oak. The highest drought sensitivity was found in Waldsieversdorf with significant positive correlations for SPEI in June and July for all provenances. In Dunkelsdorf, summer drought sensitivity was highest for German provenances, while most provenances from the natural distribution in Waechtersbach showed a strong correlation with spring drought, as indicated by positive correlations with SPEI in April (Figure 2; Supplementary Figure 5). In Waechtersbach, climate-growth relationships furthermore showed strong dependencies of red oak on moisture conditions in September of the previous year, as indicated by positive correlations with precipitation and negative correlations with temperature (Figure 2). In Dunkelsdorf, provenances from Germany and the United States had negative correlations with the moisture conditions in October of the previous year, while the influence of the previous year was not verifiable in Waldsieversdorf. Correlations with early-growing (March to May) mean and maximum temperatures differed considerably between sites. While provenances in Waechtersbach and Waldsieversdorf showed significantly positive correlations in May and March respectively, provenances in Dunkelsdorf had negative correlations in April with significant dependencies of those from Germany (Figure 2). Within sites, provenances showed a common response according to their origin (e.g., Canadian provenances in Waechtersbach, German provenances in Dunkelsdorf), whereas the response between sites varied depending on the prevailing conditions.
Figure 2

Heatmap with bootstrapped correlation coefficients between provenance chronologies (y-axis) and monthly climate data (temperature, precipitation and SPEI) from previous-year June (jun) to current-year September (SEP). Sites are arranged according to the precipitation gradient from wet (Waechtersbach) to dry (Waldsieversdorf). Correlation coefficients range from negative (violet) to positive (green) values and asterisks indicate significant correlations.
To compare the general growth performance of the provenances as well as to identify years with (and potential climatic cause of) extreme growth responses, we visually compared BAI time series with climate deviations (Figure 3). For the latter, we focused on temperature and precipitation from May to September as well as on SPEI in the summer months (June to August). Climate deviations differed between sites according to the specific climate conditions experienced revealing years with a high drought impact (e.g., 2003 and 2018) or low temperatures (e.g., 2010). The BAI series showed a comparatively constant growth pattern over the common overlap period, but the annual increment differed between sites. The highest BAI was found for provenances growing in Dunkelsdorf with a clear differentiation between German provenances and those from the natural distribution, followed by provenances in Waechtersbach, where five of the six German provenances showed the highest growth. In Waldsieversdorf, provenances had visually the most sensitive growth pattern and the overall lowest BAI, especially in the early years. Two provenances from Canada (P7 and P21) stand out with a comparable increment to the German provenances, but with a less sensitive growth pattern. The provenances from the United States had a low BAI on all three sites. Years with growth depressions varied between sites and provenances in frequency and intensity. Only in 2010, provenances on all three sites showed a negative response associated with low temperatures in the growing season. Site-specific drought years with a negative deviation in SPEI and precipitation (2003, 2015, 2018) displayed different responses in BAI series across provenances and sites.
Figure 3

Visual comparison between standardized climate variables and the basal area increment (BAI) [cm²] respectively (note different scales). As climate variables, the precipitation (P) and temperature (T) from May to September as well as SPEI in summer (Jun-Aug) indicate drought and temperature deviations during the growing season. Sites are ordered along the precipitation gradient from wet to dry.
3.3 Resistance and tree growth
The visualization of resistance revealed a plasticity of growth responses to drought with a pronounced variation between sites, provenances and drought years (Figure 4). Within-year variation was high, with changes in provenance ranks between years. The overall highest resistance to drought was found in Waechtersbach for the severe drought years 2011 and 2014 showing resistance values > 1.0 (Supplementary Table 2), which indicates that there was no growth depression during this extreme drought. In the extreme drought year 2015, a growth depression was observed, but with lower variation in resistance between provenances. In contrast, resistance to late frost was lower and German provenances had the highest resistance. In Dunkelsdorf, the lowest resistance was found in the severe drought year 2003 with a low intra-specific variation. The response of the Canadian provenances in 2018 differed from that of their counterparts, with resistance values > 1.0. Resistance in 2010 was lower for the provenances from the natural distribution, while provenances from Germany had a higher frost hardiness. The variation between drought years was most pronounced in Waldsieversdorf. Provenances from the United States showed considerable rank changes between the drought years with no growth decrease in the extreme drought year 2016 (Supplementary Figure 6). Across drought years, resistance was lowest in the ‘severe’ drought year 2003. At this site, provenances from Germany had overall the lowest resistance to drought. Provenances in Waldsieversdorf, however, suffered most during the late frost event in 2010 resulting in the lowest resistance overall (Figure 4; Supplementary Table 2).
Figure 4

Plasticity of the growth response in site-specific EYs separated between drought and frost events. Lines between EYs are drawn for visibility of interaction and indicate no time-series. Standard errors were omitted for a better visibility (presented in Supplementary Table 2).
The distinct rank changes of the provenances resulted in strong visible interactions between drought years. Overall, provenances from the same geographic origin revealed a common response to drought events, especially in Dunkelsdorf. The growth response during the late frost event resulted in a strong growth depression, with provenances from Germany showing the highest frost hardiness.
The ANOVA revealed significant differences for resistance to late frost between provenances and sites as well as a significant provenance × site interaction with the highest explained variance for sites (Supplementary Table 3). For the mean resistance in drought years, provenances and sites showed significant differences with lower explained variance, but no interaction.
We found a significantly positive correlation (R² = 0.498, p < 0.001) between resistance to late frost and diameter at breast height (Figure 5A), i.e., provenances with a high absolute growth show a high frost hardiness. The growth differentiation between German and North American provenances was most pronounced in Waechtersbach and Dunkelsdorf, which also showed high resistance values (Supplementary Figure 6). Differences between sites were significant with the highest resistance to late frost at the oceanic site Dunkelsdorf, followed by Waechtersbach and Waldsieversdorf, the latter with a lower variation between provenances (Figure 5B). On this site, provenances showed similar resistance values with lowest values for provenances from the United States.
Figure 5

Resistance (Rt) per provenance to late frost (2010) is plotted against the mean diameter at breast height (DBH) (A) and at each site (B). In the lower panels, mean Rt for site-specific drought years is plotted against the DBH (C) and at each site (D). Point shapes refer to the three sites and line types illustrate significant (solid) or non-significant (dashed) trends. Standard errors of the means were omitted for a better visibility (presented in Supplementary Table 2). Significant differences between the site means by Kruskal-Wallis test are indicated by *p < 0.05, **p < 0.01, ***p < 0.001.
However, we found no evidence for a trade-off between growth and mean resistance to drought events (R² = 0.008, p = 0.609) (Figure 5C). Although, we observed a decreasing trend between growth and resistance, this trend was not significant and the response of provenances varied across sites with significant differences between all sites. Provenances in Dunkelsdorf showed the strongest growth depression, while the highest resistance values could be observed in Waechtersbach (Figure 5D). Overall, the variation of resistance was smaller compared to the resistance to late frost. Similar trends for the response to frost and drought events can be observed when analyzing the resistance indices at the level of individual trees (Supplementary Figure 7).
4 Discussion
4.1 Spatial variation in growth response
We found considerable differences in the growth of provenances between the three sites (Figures 3, 5), suggesting the dependence of environmental effects at spatial scales (
The remarkable differences in absolute and secondary growth between introduced provenances and those from the natural distribution as well as a high intra-specific variation are comparable to the previous forest mensuration study by
4.2 Drought and frost events constrain growth
Similar to the spatial effect on tree growth, the analysis of climate-growth relationships revealed differences in the interannual variability of climatic effects. We found summer drought to be a growth-limiting factor at all sites, as indicated by the positive correlations with SPEI in the summer months and the precipitation in June, as well as negative correlations with temperature in June (Waechtersbach and Waldsieversdorf) and July (Dunkelsdorf) (Figure 2). The highest drought sensitivity was observed at the continental site with the lowest precipitation and the highest temperatures, which has been demonstrated in other studies with different tree species (
The identified drought years according to SPEI varied between the three sites. While we detected two consistent years (2003 and 2018; see also
The high variation in the response of the provenances to drought events between drought years may be impacted by an intra-specific growth response (Figure 4). The strong interaction effects between drought years can be explained by their difference in intensity and occurrence (different months), and visualized the heterogenous impact of different drought events on tree growth (
In contrast to drought years, which differed between sites, we analyzed the growth response in 2010 for all three sites. This year was characterized by generally low temperatures and a late frost event in May (Supplementary Figure 3; see also
4.3 High risk, high gain?
Surprisingly, our results indicate no trade-off between growth and resistance to frost hardiness, which contradicts the expected ‘high risk, high gain’ -strategy. We found that provenances with a high growth also have a high frost hardiness and in accordance therewith, provenances on the continental site with the lowest productivity had the highest growth depression during the late frost event (Figure 5A). Further, we found no (significant) evidence for a trade-off between growth and resistance to drought (Figure 5C). However, the drought response varied less between provenances within sites compared to the response to late frost. The absence of a drought hardiness trade-off was also observed for Douglas fir in its natural distribution (
Trade-offs between growth and resistance to drought and frost are a common observation for other tree species, which mainly showed low growth with increasing drought tolerance or frost hardiness (
5 Conclusion
For forest management and plant breeders, provenances with high growth and a high resistance to drought and frost events would be beneficial and have important implications, as they provide suitable reproductive material for future climate conditions (
However, further investigations like wood anatomical analyses can be helpful in providing information about the cell structure and water use efficiency, and thus explanations of the different responses of provenances and their adaptive strategies. Selecting introduced provenances from the analyzed sites may reduce the risk of frost injuries, which would not jeopardize the drought tolerance in consideration of their superior growth performance. Understanding how populations of introduced tree species adapt to the local environments and respond to increasing drought and frost events will be essential under future climate conditions.
Statements
Data availability statement
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Author contributions
JMK: Formal Analysis, Investigation, Methodology, Writing – original draft, Data curation, Validation, Visualization. EM: Methodology, Supervision, Validation, Writing – review & editing. ML: Conceptualization, Funding acquisition, Project administration, Supervision, Writing – review & editing. KJL: Conceptualization, Project administration, Visualization, Writing – review & editing. MMT: Methodology, Supervision, Validation, Visualization, Writing – review & editing.
Funding
The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study is part of the project “RubraSelect” founded by the German Federal Ministry of Food and Agriculture and the Federal Ministry of the Environment, Nature Conservation, Nuclear Safety and Consumer Protection following a decision of the German Bundestag (Waldklimafonds, grant number 2220WK03C4).
Acknowledgments
We acknowledge the technical staff for the long-term support and measurement of the sites including the data acquisition, which enables studies like this, and the forest enterprises offering and managing the test sites. We would also like to thank all those who have contributed to this study, whether in the form of comments or answering questions. The Article Processing Charge (APC) was funded by the joint publication funds of the TU Dresden, including Carl Gustav Carus Faculty of Medicine, and the SLUB Dresden as well as the Open Access Publication Funding of the DFG.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpls.2024.1374498/full#supplementary-material
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Summary
Keywords
dendroecology, tree rings, climate-growth relationships, provenance trial, introduced species, frost hardiness, drought hardiness
Citation
Kormann JM, van der Maaten E, Liesebach M, Liepe KJ and van der Maaten-Theunissen M (2024) High risk, high gain? Trade-offs between growth and resistance to extreme events differ in northern red oak (Quercus rubra L.). Front. Plant Sci. 15:1374498. doi: 10.3389/fpls.2024.1374498
Received
22 January 2024
Accepted
25 March 2024
Published
05 April 2024
Volume
15 - 2024
Edited by
Sergio Rossi, Université du Québec à Chicoutimi, Canada
Reviewed by
Jozica Gricar, Slovenian Forestry Institute, Slovenia
Rosario Guzmán-Marín, Université du Québec à Chicoutimi, Canada
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© 2024 Kormann, van der Maaten, Liesebach, Liepe and van der Maaten-Theunissen.
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*Correspondence: Jonathan M. Kormann, jonathan.kormann@thuenen.de
†ORCID: Jonathan M. Kormann, orcid.org/0000-0002-9242-4016; Ernst van der Maaten, orcid.org/0000-0002-5218-6682; Mirko Liesebach, orcid.org/0000-0001-8840-5026; Katharina J. Liepe, orcid.org/0000-0003-0511-4325; Marieke van der Maaten-Theunissen, orcid.org/0000-0002-2942-9180
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