Extreme droughts are occurring more frequently in Central Europe, resulting in elevated tree mortality and the need for reforestation and forest conversion. While Douglas-fir (Pseudotsuga menziesii) is considered a potential candidate for future climate-resilient forests, in the past this non-native crop tree species was selected for productivity rather than stress resistance. Here, we performed dendrochronological analyses in mature trees from 50 Douglas-fir provenances across six sites in Southern Germany, covering a precipitation gradient of 542 mm yr-1. Because the provenances were not equally distributed across the gradient, they were divided into three groups according to their climate at origin. We observed high variability both in radial increment and radial growth patterns between the provenances, which were lowest for the northern-interior provenances but unrelated to the precipitation gradient. As expected, the extreme drought events in 2003 and 2018 significantly reduced the radial growth of all provenances, with the northern-interior provenances showing strongest reductions and therefore lowest growth resistance. However, the recovery of radial growth was equal to the coastal origins after 2003 and even higher after 2018. This combination of low resistance and high recovery is consistent with a higher tree-ring plasticity. Furthermore, we found a positive relationship between resilience and resistance, in contrast to the general trend reported for conifers. In conclusion, northern-interior provenances showed a higher plastic growth response to extreme drought. While Douglas-fir appears to be a promising candidate for future climate-resilient forests, at least at our relatively wet sites, further validation is needed to confirm whether interior provenances are better drought adapted than coastal provenances

The severe drought of 2018/19 caused widespread early discoloration, defoliation and tree mortality in European beech (Fagus sylvatica L.), although local drought responses varied strongly among coexisting trees. To identify potential drivers, we investigated 520 mature beech trees across 20 forest sites dominated by European beech in Southern Germany, Central Europe. We recorded crown health conditions and described the small-scale variability in the topographic, edaphic, structural and competitional status of individual trees, complemented by dendrochronological sampling. Overall, tall trees growing on sites with more available soil water and higher pre-drought growth showed highest defoliation rates, supporting global findings that larger trees are more susceptible to drought-induced tree mortality. In the ordered beta-regression model, including forest sites as random effect, pre-existing canopy gaps significantly improved vitality during drought and beech tended to show lower defoliation in mixed stands with Scots pine. These findings highlight canopy and neighbourhood structure as a possible buffer against drought stress. By contrast, the influence of tree size and soil water availability could not be detected in the model due to a large variability across sites. A substantial portion of the remaining small-scale variation in defoliation could not be explained by our fixed effects, but rather by site effects, underlining the complexity of drought responses in beech forests. We conclude that for future-proofing our forests, selective thinning of large European beech trees in non-drought years appears to be an appropriate silvicultural measure to strengthen the drought resilience of neighbouring trees, which deserves further testing. Furthermore, silvicultural management actions should account for species mixtures while explicitly considering species-specific drought response strategies, for example by combining species with contrasting hydraulic strategies or rooting systems.

Summer droughts have affected tree growth in central Europe since at least the 1940s, yet the physiological mechanisms behind why some trees die whilst others survive remain poorly understood. Here, we present absolutely dated and annually resolved tree-ring width, carbon (δ13C) and oxygen (δ18O) stable isotope chronologies from 18 Scots pines (Pinus sylvestris L.) growing near the species' climatic and edaphic limit in one of Germany's driest regions (Rhine Hesse, near Mainz). Spanning the period 1930-2019, sampled trees were assigned to three post-2018 vitality classes based on crown transparency: vigorous, intermediate and poor vigour (including dead individuals). We assessed long-term growth and isotopic trajectories in relation to climate variables, with a focus on pan-European summer drought extremes in 1947, 1976, 2003 and 2018. We found that trees with consistently higher growth rates and elevated long-term δ13C values were more susceptible to dieback, whereas surviving trees maintained lower δ13C values. This pattern suggests differences in long-term water-use strategies and/or drought exposure, whilst also partly reflecting canopy position and light-driven assimilation. In contrast, δ18O values sharply increased during drought events, especially in poor-vigour trees, indicating greater reliance on shallow, evaporatively enriched water sources and heightened hydraulic strain under extreme drought. These isotopic trajectories differentiated vitality classes well before visible canopy decline. Our findings indicate that the 2018 drought was not the sole trigger, but rather a tipping point in a long-term dieback process driven by repeated droughts and heatwaves. Tree-ring stable isotopes, particularly when interpreted alongside growth trajectories, provide valuable early warning signals of physiological stress and drought vulnerability. Since trees with conservative growth strategies were more resilient, long-term physiological stability, rather than maximum productivity, may enhance forest resilience under an increasingly warm, dry and variable future climate.

Abstract European beech (Fagus sylvatica L.), one of the most important deciduous timber species in Central Europe, experienced widespread crown defoliation and tree mortality during the severe drought in 2018/19, but responses varied strongly among individuals. Canopy gaps were found to be one driver of this variability. In this study, we investigated how the size, orientation, and the temporal dynamics of canopy gaps and open areas affect crown defoliation in European beech during the 2018/19 drought across 19 beech-dominated sites in Bavaria, Germany. To quantify canopy gap dynamics around individual beech target trees, we derived gap area metrics from multitemporal digital surface models derived from orthophotos across three timesteps. For each target tree, total canopy gap area was calculated within a 15 m buffer. To capture directional effects, the gap area was additionally partitioned into eight cardinal and intercardinal directions, allowing us to characterize the spatial configuration of gaps relative to each tree. Our results indicate that trees exposed to gaps on their western side (meaning the tree was located at the eastern edge of the gap) exhibited significantly higher defoliation, highlighting possible combined influences of higher exposure to wind and solar radiation. In contrast, gaps towards the north of the trees were associated with lower defoliation. Increases in gap area between 2013/14 and 2019 towards the southwest were linked to higher drought stress. While the gap-related predictors explained only a modest proportion of the total variability, site-level differences in general conditions accounted for a substantially larger portion. Our findings demonstrate the potential of digital surface models from orthophotos as a reproducible, remote sensing-based workflow for capturing detailed spatial and temporal canopy gap dynamics across forest sites. For practical management, the directional orientation of canopy openings should be considered when planning silvicultural interventions, as western and southwestern exposures may increase drought vulnerability of valuable target trees.

The increasing frequency of drought events in recent years has become a major hurdle for reforesting forests after natural disturbances in many areas globally, including parts of Central Europe. As an example, reforestation projects after bark beetle disturbances have faced notable failures and losses due to prolonged drought conditions in Northern Bavaria (Germany). Irrigation is a potential measure increasing reforestation success and is currently funded by the regional government. However, historically irrigation was not a common technique in this area and there is a lack of both practical and scientific knowledge concerning irrigation strategies. The optimal timing for the irrigation of the saplings as well as the water amount applied are crucial aspects in this context. This study addresses this knowledge gap by conducting a drought stress experiment within a greenhouse environment, focusing on four commonly planted tree species prevalent in our study region in northern Bavaria. Various approaches were explored to reliably detect drought stress and identify the irrigation demand both concerning timing and amount of water applied: the experimental design integrates environmental data with ecophysiological measurements and employs drought stress indices derived from close-range remote sensing. The most promising methodology for detecting the irrigation demand, identified through rigorous experimentation, will be further explored on forest sites post-planting. Implementing such optimized irrigation strategies holds promise for safeguarding reforestation endeavors, particularly in regions prone to drought, and contributes to the sustainable management of forest ecosystems and water usage.

Increasingly frequent and intense drought events can jeopardize the current and future productivity and health of forests. Consequently, the ability of dynamic vegetation models (DVMs) to simulate drought impacts is paramount to improving their representation of the carbon cycle. To capture the physiological damage inflicted by drought, many state-of-the-art DVMs have implemented representations of plant hydraulic architecture in recent years. Although the understanding of the underlying processes governing hydrodynamic behavior in plants has steadily increased, the parameterization of hydraulic traits for different plant functional types (PFTs) remains a source of uncertainty in model output – in part due to limited data availability. Here, we use LPJ-GUESS-HYD, an extension of LPJ-GUESS with new parameters and processes to simulate plant hydraulic architecture, isohydrodynamic water-potential regulation, and hydraulic failure mortality. Using latin hypercube sampling we create 6000 sets of hydraulic parameter combinations based on values found in the literature. Based on these parameter sets, we conduct a comprehensive variance-based sensitivity analysis for a set of 12 common European tree species across 37 sites from the FLUXNET 2020 warm winter dataset, encompassing a wide range of European ecosystems. Subsequently, we determine which parameters and parameter interactions contribute the most to variations in model outputs. Our results indicate that of the seven parameters used in the hydraulic architecture model of LPJ-GUESS-HYD, only a few have a significant effect on the model outcomes. More specifically, Ѱ50, the water potential at which 50 percent of conductance is lost, and maximum specific leaf conductance had the largest impact on simulated processes. Parameters related with the isohydric strategy of plants, had a lesser but still substantial role in shaping the model output. These results suggest that certain hydraulic parameters – and combinations thereof – play a disproportionate role in modulating simulated forest fluxes and states in LPJ-GUESS-HYD. Specific parameterization choices can drastically alter model performance, including whether PFTs can survive in a given climate or not. Aside from encouraging careful consideration of the available trait data when parameterizing new PFTs, our results may guide future experiments in choosing which hydraulic traits to focus on.

The recent intensification of hotter droughts due to climate change has resulted in a reduced resilience of forests at global scale. This response is not only mirrored by increasing rates of tree dieback, but also reflected in a reduced canopy greenness (Buras et al., 2021) as well as emerging statistical early-warning signals of declining forest resilience (EWS, Forzieri et al., 2022). Yet, a systematic investigation on how atmospheric water demand, canopy greenness decline, and EWS are linked across European forests and including the most recent extreme droughts of 2022 and 2023 is missing. To overcome this research gap, we 1) deployed time series of remotely sensed canopy greenness (NDVI) at moderate spatial resolution (6.25 ha) over the period 2001-2023 for the European continent, 2) derived three independent statistical indices of forest resilience, and 3) related these data streams to atmospheric water demand (VPD).Over the study period, VPD displayed an increasing trend over most of Europe, which was mirrored in a concurrent decline of forest canopy greenness. Moreover, we found a clear and significant non-linear negative impact of rising VPD on canopy greenness for 75% of European forests. The grid-specific frequency of identified EWS was significantly linked to VPD and featured a record extent in 2023 with about one fifth of European forests being affected. This observation was independently supported by a strong increase in the spatiotemporal memory of canopy greenness since the extreme drought of 2018 (Buras et al., 2020). Finally, in the years following 2018 VPD-based predictions increasingly overestimated canopy greenness, hinting at forests decreasing ability to recover from extreme drought impacts. In conclusion, our study underscores the enhanced vulnerability of European forests during the extraordinarily dry period 2018-2023 with important implications for forestry, land-based mitigation plans, and regional climate feedbacks. Buras, A., Rammig, A., Zang, C.S., 2021. The European Forest Condition Monitor: Using Remotely Sensed Forest Greenness to Identify Hot Spots of Forest Decline. Frontiers in Plant Science 12, 2355. https://doi.org/10.3389/fpls.2021.689220Buras, A., Rammig, A., Zang, C.S., 2020. Quantifying impacts of the 2018 drought on European ecosystems in comparison to 2003. Biogeosciences 17, 1655–1672. https://doi.org/10.5194/bg-17-1655-2020Forzieri, G., Dakos, V., McDowell, N.G., Ramdane, A., Cescatti, A., 2022. Emerging signals of declining forest resilience under climate change. Nature 608, 534–539. https://doi.org/10.1038/s41586-022-04959-9

Dry and warm climate conditions in southern Europe represent clear limits for European beech (Fagus sylvatica) growth near the species southern distribution limit, but it is unclear how aridification and changes in seasonal precipitation regimes will affect these forests at the individual level. We explored climate-growth relationships and the seasonality of peak climate signals in European beech using daily climate data and a large collection of tree-ring width series from southern and southeastern Europe through Generalised Linear Mixed Models (GLMMs). In most cases we found a positive and significant influence of precipitation on tree growth, and a significant negative effect of maximum temperature. Predictions from the GLMMs revealed a positive impact of precipitation during an 88 day window from spring to early summer (mid-April to mid-July), for an average tree across our network. This critical growing time window ranged from 75 days in warmer and drier conditions, and extended up to 100 days in areas with mild temperatures and moderate summer precipitation. Maximum temperatures negatively affected trees for an average of 27 day window in summer (June-July). This period was reduced to <10 days in locations with wetter and colder summers, rising up to 45 days in sites with drier and warmer summers. The positive effect of precipitation on growth was stronger and commenced earlier in larger trees. Similarly, the negative effects of maximum temperatures were more pronounced for larger trees. The use of daily climate data and a tree-centred approach allowed for capturing critical temporal dynamics in climate-growth relationships that are often overlooked by conventional methods. These insights significantly enhance our understanding of climatic factors influencing individual beech growth at the edge of its distribution range and their seasonal variations.

Climate change is strongly influencing global shifts in forest ecosystem dynamics. There has been a twofold increase in canopy mortality within the temperate forests of Europe in the past thirty years. The trend has been further intensified by recent drought episodes occurring between 2018 and 2020, leading to increased instances of die-offs and reduced vitality among key tree species. In central Europe, notably in Germany, European beech (Fagus sylvatica L.) stands out as a tree species with high ecological and economic significance. Recent severe drought conditions led to substantial vitality loss and mortality. Nevertheless, there was considerable diversity in how individual beech trees responded to drought, with some trees in the same location being heavily impacted while others remained seemingly unaffected. Factors influencing this uneven response are still not fully understood. In this study, we gathered 600 beech tree-ring width series from 13 sites located across Northern Bavaria, along a climatic gradient. We explore the differences in growth between two groups of trees (damaged/vital) using a dendroecological approach. We evaluated loss of vitality through the implementation of mortality and critical slowdown indicators such as long-term growth decline or changes in climate memory, as well as climate/growth relations and growth synchrony indicative of changing growth limitations. While we did not find significant differences between groups in terms of climate memory and drought sensitivity, our results showed a divergence in the growth patterns of vital and damaged trees following repetitive exposure to drought events. We detected higher growth rates of damaged trees prior to the last three decades, after which their growth rates declined stronger than vital trees. Our results suggest that faster-growing beech trees may be more susceptible to drought-induced mortality, which is in line with findings of higher vulnerability of faster-growing trees to environmental stressors.

Due to climate change, severe-drought events have become increasingly commonplace across Europe in recent decades, with future projections indicating that this trend will likely continue, posing questions about the continued viability of European forests. Observations from the most recent pan-European droughts suggest that these types of “hotter droughts” may acutely alter the carbon balance of European forest ecosystems. However, substantial uncertainty remains regarding the possible future impacts of severe drought on the European forest carbon sink. Dynamic vegetation models can help to shed light on such uncertainties; however, the inclusion of dedicated plant hydraulic architecture modules in these has only recently become more widespread. Such developments intended to improve model performance also tend to add substantial complexity, yet the sensitivity of the models to newly introduced processes is often left undetermined. Here, we describe and evaluate the recently developed mechanistic plant hydraulic architecture version of LPJ-GUESS and provide a parameterization for 12 common European forest tree species. We quantify the uncertainty introduced by the new processes using a variance-based global sensitivity analysis. Additionally, we evaluate the model against water and carbon fluxes from a network of eddy covariance flux sites across Europe. Our results indicate that the new model is able to capture drought-induced patterns of evapotranspiration along an isohydric gradient and manages to reproduce flux observations during drought better than standard LPJ-GUESS does. Further, the sensitivity analysis suggests that hydraulic process related to hydraulic failure and stomatal regulation play the largest roles in shaping the model response to drought.

The prospect for European beech forests (Fagus sylvatica L.) over the course of the 21st century is uncertain due to climate change. In context, climate sensitivity of growth is a valuable indicator of physiological integrity, but its natural variability is poorly understood in productive, closed canopy forests. Climate sensitivity may not only depend on temporal and spatial differences in climatic conditions, but also on trees’ rank progression in the course of forest maturation. Here, we determine how the drought sensitivity of secondary growth in beech varies in space and time according to growth trends, growth variability and climatic conditions. The temporal variability of these variables is determined via a moving window approach using a network of tree-ring sites across the species’ geographical and climatological distribution. The moving window derived variables are applied to a linear mixed-effects model allowing for the estimation of linear, non-linear and interactive effects. Furthermore, dry and wet subsets of the data are supplied individually to determine differences between dry and wet site conditions. Our results indicate considerable variability in climate sensitivity due to complex non-linear and interactive effects of all variables. Generally, drought sensitivity is strongly and positively coupled with growth variability and climatic aridity. The strong non-linear and interactive effects between all variables result in drought sensitivity changing considerably with changes in growth variability and growth trends when climatic conditions are average or wetter than average. However, during dry time-periods, drought sensitivity is consistently high and decoupled from changes in growth trends and growth variability. While these patterns remain relatively similar between dry and wet sites, dry sites show significantly higher drought sensitivity compared to wet sites overall. In conclusion, we found beech’s drought sensitivity to be significantly affected by growth variability, growth trends and climatic conditions. Furthermore, the influence of each variable on drought sensitivity changes drastically as they interact, indicating all these factors need to be considered when interpreting beech’s climate sensitivity.

In numerous ecological systems, forthcoming critical transitions can be identified using a variety of methods for deriving early warning indicators. Several methods focus on characteristics of time-series related to system behaviour or properties, including changes in time-series variability. One such method is conditional heteroskedasticity (CH). CH defines a time series as having a non-constant variability, that is also dependent on the variability at previous time-steps, where increases in variability indicate that the system under study is nearing a critical transition. Here, we apply this concept to time series of radial growth, measured as tree-ring widths: a general autoregressive conditional heteroskedasticity (GARCH) model is used to produce a CH time-series from detrended tree-ring data. By analysing the variability trends within this time series, conclusions can be made relating to the system’s proximity to transition. Whilst this form of analysis is not a novel concept in the field of ecology, such a thorough examination of the models’ ability to detect change in the variability of tree-ring data is yet to be carried out. We propose the application of a dual-model approach, using both GARCH and VS-Lite models, with an aim of determining the efficacy of such a strategy to detect not only changes in tree-growth stability, but more specifically changes induced by climate stressors. This approach has the potential to forecast impending critical transitions in tree-growth behaviour, possible fluctuations in the rate of mortality, and quantify the influence of climate on growth stability at both the tree and site-level.

With ongoing global warming, increasing water deficits promote physiological stress on forest ecosystems with negative impacts on tree growth, vitality, and survival. How individual tree species will react to increased drought stress is therefore a key research question to address for carbon accounting and the development of climate change mitigation strategies. Recent tree-ring studies have shown that trees at higher latitudes will benefit from warmer temperatures, yet this is likely highly species-dependent and less well-known for more temperate tree species. Using a unique pan-European tree-ring network of 26,430 European beech (Fagus sylvatica L.) trees from 2118 sites, we applied a linear mixed-effects modeling framework to (i) explain variation in climate-dependent growth and (ii) project growth for the near future (2021-2050) across the entire distribution of beech. We modeled the spatial pattern of radial growth responses to annually varying climate as a function of mean climate conditions (mean annual temperature, mean annual climatic water balance, and continentality). Over the calibration period (1952-2011), the model yielded high regional explanatory power (R2 = 0.38-0.72). Considering a moderate climate change scenario (CMIP6 SSP2-4.5), beech growth is projected to decrease in the future across most of its distribution range. In particular, projected growth decreases by 12%-18% (interquartile range) in northwestern Central Europe and by 11%-21% in the Mediterranean region. In contrast, climate-driven growth increases are limited to around 13% of the current occurrence, where the historical mean annual temperature was below ~6°C. More specifically, the model predicts a 3%-24% growth increase in the high-elevation clusters of the Alps and Carpathian Arc. Notably, we find little potential for future growth increases (-10 to +2%) at the poleward leading edge in southern Scandinavia. Because in this region beech growth is found to be primarily water-limited, a northward shift in its distributional range will be constrained by water availability.

Increasingly frequent and intense drought events can jeopardize the current and future productivity and health of forests. Consequently, the ability of dynamic vegetation models (DVMs) to simulate drought impacts is paramount to improving their representation of the carbon cycle. To capture the physiological damage inflicted by drought, many state-of-the-art DVMs have implemented representations of plant hydraulic architecture in recent years. Although the understanding of the underlying processes governing hydrodynamic behavior in plants has steadily increased, the parameterization of hydraulic traits for different plant functional types (PFTs) remains a source of uncertainty in model output – in part due to limited data availability.    Here, we use LPJ-GUESS-HYD, an extension of LPJ-GUESS with new parameters and processes to simulate plant hydraulic architecture, isohydrodynamic water-potential regulation, and hydraulic failure mortality. Using latin hypercube sampling we create 6000 sets of hydraulic parameter combinations based on values found in the literature. Based on these parameter sets, we conduct a comprehensive variance-based sensitivity analysis for a set of 12 common European tree species across 37 sites from the FLUXNET 2020 warm winter dataset, encompassing a wide range of European ecosystems. Subsequently, we determine which parameters and parameter interactions contribute the most to variations in model outputs.    Our results indicate that of the seven parameters used in the hydraulic architecture model of LPJ-GUESS-HYD, only a few have a significant effect on the model outcomes. More specifically, Ѱ50, the water potential at which 50 percent of conductance is lost, and maximum specific leaf conductance had the largest impact on simulated processes. Parameters related with the isohydric strategy of plants, had a lesser but still substantial role in shaping the model output.    These results suggest that certain hydraulic parameters – and combinations thereof –  play a disproportionate role in modulating simulated forest fluxes and states in LPJ-GUESS-HYD. Specific parameterization choices can drastically alter model performance, including whether PFTs can survive in a given climate or not. Aside from encouraging careful consideration of the available trait data when parameterizing new PFTs, our results may guide future experiments in choosing which hydraulic traits to focus on.

The Amazon rainforest is highly biodiverse and has the largest extent of the remaining intacttropical forests in the world. To this day, undisturbed tropical forests act as a carbon sink by takingup about 15% of anthropogenic carbon emissions per year. However, in the past decades, adeclining trend in the carbon sink capacity in the Amazon rainforest has been observed due toincreased carbon losses and tree mortality. The causes are disputed, but increasing temperaturesand more frequent severe droughts are potentially major drivers. We employ a novel modelingframework and hypothesize that previously rare, extreme droughts in the Amazon, such as theones in 2005 and 2010, constitute the main cause behind the decline of the net carbon sink inaboveground biomass. Our dynamic vegetation model simulates process-based plant hydraulicsand drought-induced mortality, and accounts for the diversity of strategies in plant responses todrought based on observed hydraulic vulnerability curves. The simulated impact of the 2005drought event temporarily turned the annual Amazon net carbon sink to a carbon source of about0.25MgCha-1. In contrast to other dynamic vegetation models our model simulated anincreasing trend in carbon losses and a declining trend in the Amazon carbon sink over the past25 years (net sink rate of-0.015MgCha-1year-1or-0.18MgCha-1per decade) whichcorresponds well with long-term forest monitoring data (net sink rate of-0.016MgCha-1year-1). We show that this trend is entirely attributable to drought-induced forest mortalityduring extreme years. The simulations show a threshold-like behavior between drought intensityand biomass loss, which is due to xylem vulnerability, indicating the potentially high sensitivity ofAmazon forests to extreme drought. Further increases in the severity and frequency of droughtsmight thus lead to greater carbon release and tree mortality than previously assumed.

Abstract In times of more frequent global change‐type droughts and associated tree mortality events, competition release is one silvicultural measure discussed to have an impact on the resilience of managed forest stands. Understanding how trees compete with each other is therefore crucial, but different measurement options and competition indices (CI) leave users with a difficult choice, as no single competition index has proven universally superior. To help users with the choice and computation of appropriate indices, we present the open‐source TreeCompR package, which handles 3D point clouds and classical forest inventory data, enabling the calculation of both innovative point cloud‐based indices and traditional distance‐dependent indices. It serves as a centralized platform for exploring and comparing different CIs, allowing users to test and select the most suitable CI for their specific research questions within a common interface. To evaluate the package, we used TreeCompR to quantify the competition situation of 307 European beech trees from 13 sites in Central Europe. Based on this dataset, we discuss the interpretation, comparability and sensitivity of the different indices to their parameterization and identify possible sources of uncertainty and ways to minimize them. The compatibility of TreeCompR with different data formats and different data collection methods makes it accessible and useful for a wide range of users, specifically ecologists and foresters. Due to the flexibility in the choice of input formats as well as the emphasis on tidy, well‐structured output, our package can easily be integrated into existing data‐analysis workflows both for 3D point cloud and classical forest inventory data.

The future performance of the widely abundant European beech (Fagus sylvatica L.) across its ecological amplitude is uncertain. Although beech is considered drought-sensitive and thus negatively affected by drought events, scientific evidence indicating increasing drought vulnerability under climate change on a cross-regional scale remains elusive. While evaluating changes in climate sensitivity of secondary growth offers a promising avenue, studies from productive, closed-canopy forests suffer from knowledge gaps, especially regarding the natural variability of climate sensitivity and how it relates to radial growth as an indicator of tree vitality. Since beech is sensitive to drought, we in this study use a drought index as a climate variable to account for the combined effects of temperature and water availability and explore how the drought sensitivity of secondary growth varies temporally in dependence on growth variability, growth trends, and climatic water availability across the species' ecological amplitude.Our results show that drought sensitivity is highly variable and non-stationary, though consistently higher at dry sites compared to moist sites. Increasing drought sensitivity can largely be explained by increasing climatic aridity, especially as it is exacerbated by climate change and trees' rank progression within forest communities, as (co-)dominant trees are more sensitive to extra-canopy climatic conditions than trees embedded in understories. However, during the driest periods of the 20th century, growth showed clear signs of being decoupled from climate. This may indicate fundamental changes in system behavior and be early-warning signals of decreasing drought tolerance. The multiple significant interaction terms in our model elucidate the complexity of European beech's drought sensitivity, which needs to be taken into consideration when assessing this species' response to climate change.

Late-spring frost (LSF) is a critical factor influencing the functioning of temperate forest ecosystems. Frost damage in the form of canopy defoliation impedes the ability of trees to effectively photosynthesize, thereby reducing tree productivity. In recent decades, LSF frequency has increased across Europe, likely intensified by the effects of climate change. With increasing warming, many deciduous tree species have shifted towards earlier budburst and leaf development. The earlier start of the growing season not only facilitates forest productivity but also lengthens the period during which trees are most susceptible to LSF. Moreover, recent forest transformation efforts in Europe intended to increase forest resilience to climate change have focused on increasing the share of deciduous species in forests. To assess the ability of forests to remain productive under climate change, dynamic vegetation models (DVMs) have proven to be useful tools. Currently, however, most state-of-the-art DVMs do not model processes related to LSF and the associated impacts. Here, we present a novel LSF module for integration with the dynamic vegetation model Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS). This new model implementation, termed LPJ-GUESS-FROST, provides the ability to directly attribute simulated impacts on forest productivity dynamics to LSF. We use the example of European beech, one of the dominant deciduous species in central Europe, to demonstrate the functioning of our novel LSF module. Using a network of tree-ring observations from past frost events, we show that LPJ-GUESS-FROST can reproduce productivity reductions caused by LSF. Further, to exemplify the effects of including LSF dynamics in DVMs, we run LPJ-GUESS-FROST for a study region in southern Germany for which high-resolution climate observations are available. Here, we show that modeled LSF plays a substantial role in regulating regional net primary production (NPP) and biomass dynamics, emphasizing the need for LSF to be more widely accounted for in DVMs.

The data accompany the publication "Kuhl et al. 2023: Using Machine Learning on tree-ring data to determine the geographical provenance of historical construction timbers. The data are the raw model inputs and allow a reconstruction of the models mentioned and used in the paper. Please contact the authors if you would like to collaborate on a project using these data. If comments or questions arise, please contact Eileen Kuhl (eikuhl@uni-mainz.de).

Understanding tree-response to extreme drought events is imperative for maintaining forest ecosystem services under climate change. While tree-ring derived secondary growth measurements are often used to estimate direct and lagging drought impacts, so-called drought legacies, underlying physiological responses remain difficult to constrain across species and site conditions. As extreme droughts may alter the functioning of plants in terms of resource allocation being shifted towards repair and physiological adjustments, climate control on growth may consequently be altered until physiological recovery is completed. In this context, we here advance the concept of drought legacy effects by quantifying ‘functional legacies’ as climate sensitivity deviations (CSD) of secondary growth after droughts, i.e. temporary alterations of climate-growth relations. We quantified climate sensitivity deviations after extreme drought events by applying linear mixed-effects models to a global-scale, multi-species tree-ring dataset and differentiated responses by clades, site aridity and hydraulic safety margins (HSMs). We found that while direct secondary growth legacies were common across these groups, responses in post-drought climate sensitivity deviations were nuanced. Gymnosperms showed weaker coupling between secondary growth and the dominant climatic driver after droughts, a response that was narrowed down to gymnosperms with a small HSM, i.e. risky hydraulic strategy. In comparison, angiosperms instead showed stronger coupling between secondary growth and the dominant climatic driver following droughts, which was narrowed down to the angiosperms growing in arid sites. These results are consistent with current understanding of physiological impairment and carbon reallocation mechanisms, and the distinct functional responses suggest functional legacies quantified by climate sensitivity deviations is a promising avenue for detecting and thus studying physiological mechanisms underlying drought-responses in tree growth on large scales.