A harmonized database of European forest simulations under climate change.

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing. Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.

Process-oriented models of leaf senescence are biased towards the mean: Impacts on model performance and future projections.

The timing of leaf senescence in deciduous trees influences carbon uptake and the resources available for tree growth, defense, and reproduction. Therefore, simulated biosphere-atmosphere interactions and, eventually, estimates of the biospheric climate change mitigation potential are affected by the accuracy of process-oriented leaf senescence models. However, current leaf senescence models are likely to suffer from a bias towards the mean (BTM). This may lead to overly flat trends, whereby errors would increase with increasing difference from the average timing of leaf senescence, ultimately distorting model performance and projected future shifts. However, such effects of the BTM on model performance and future shifts have rarely been investigated. We analyzed >17 × 106 past dates and >49 × 106 future shifts of leaf senescence simulated by 21 process-oriented models that had been calibrated with >45,000 observations from Central Europe for three major European tree species. The surmised effects on model performance and future shifts occurred in all 21 models, revealing strong model-specific BTM. In general, the models performed only slightly better than a null model that just simulates the average timing of leaf senescence. While standard comparisons of model performance favored models with stronger BTM, future shifts of leaf senescence were smaller when projected by models with weaker BTM. Overall, the future shifts for 2090-2099 relative to 1990-1999 increased by an average of 13-14 days after correcting for the BTM. In conclusion, the BTM substantially affects simulations by state-of-the-art leaf senescence models, which compromises model comparisons and distorts projections of future shifts. Smaller shifts result from flatter trends associated with stronger BTM. Therefore, smaller shifts according to models with weaker BTM illustrate the considerable uncertainty in current leaf senescence projections. It is likely that state-of-the-art projections of future biosphere behavior under global change are distorted by erroneous leaf senescence models.

Mother trees, altruistic fungi, and the perils of plant personification.

There are growing doubts about the true role of the common mycorrhizal networks (CMN or wood wide web) connecting the roots of trees in forests. We question the claims of a substantial carbon transfer from 'mother trees' to their offspring and nearby seedlings through the CMN. Recent reviews show that evidence for the 'mother tree concept' is inconclusive or absent. The origin of this concept seems to stem from a desire to humanize plant life but can lead to misunderstandings and false interpretations and may eventually harm rather than help the commendable cause of preserving forests. Two recent books serve as examples: The Hidden Life of Trees and Finding the Mother Tree.

Tree species admixture increases ecosystem service provision in simulated spruce- and beech-dominated stands.

Climate-adaptive forest management aims to sustain the provision of multiple forest ecosystem services and biodiversity (ESB). However, it remains largely unknown how changes in adaptive silvicultural interventions affect trade-offs and synergies among ESB in the long term. We used a simulation-based sensitivity analysis to evaluate popular adaptive forest management interventions in representative Swiss low- to mid-elevation beech- and spruce-dominated forest stands. We predicted stand development across the twenty-first century using a novel empirical and temperature-sensitive single-tree forest stand simulator in a fully crossed experimental design to analyse the effects of (1) planting mixtures of Douglas-fir, oak and silver fir, (2) thinning intensity, and (3) harvesting intensity on timber production, carbon storage and biodiversity under three climate scenarios. Simulation results were evaluated in terms of multiple ESB provision, trade-offs and synergies, and individual effects of the adaptive interventions. Timber production increased on average by 45% in scenarios that included tree planting. Tree planting led to pronounced synergies among all ESBs towards the end of the twenty-first century. Increasing the thinning and harvesting intensity affected ESB provision negatively. Our simulations indicated a temperature-driven increase in growth in beech- (+ 12.5%) and spruce-dominated stands (+ 3.7%), but could not account for drought effects on forest dynamics. Our study demonstrates the advantages of multi-scenario sensitivity analysis that enables quantifying effect sizes and directions of management impacts. We showed that admixing new tree species is promising to enhance future ESB provision and synergies among them. These results support strategic decision making in forestry. Supplementary Information: The online version contains supplementary material available at 10.1007/s10342-022-01474-4.

Accuracy, realism and general applicability of European forest models.

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

The evolution, complexity and diversity of models of long-term forest dynamics.

To assess the impacts of climate change on vegetation from stand to global scales, models of forest dynamics that include tree demography are needed. Such models are now available for 50 years, but the currently existing diversity of model formulations and its evolution over time are poorly documented. This hampers systematic assessments of structural uncertainties in model-based studies.We conducted a meta-analysis of 28 models, focusing on models that were used in the past five years for climate change studies. We defined 52 model attributes in five groups (basic assumptions, growth, regeneration, mortality and soil moisture) and characterized each model according to these attributes. Analyses of model complexity and diversity included hierarchical cluster analysis and redundancy analysis.Model complexity evolved considerably over the past 50 years. Increases in complexity were largest for growth processes, while complexity of modelled establishment processes increased only moderately. Model diversity was lowest at the global scale, and highest at the landscape scale. We identified five distinct clusters of models, ranging from very simple models to models where specific attribute groups are rendered in a complex manner and models that feature high complexity across all attributes.Most models in use today are not balanced in the level of complexity with which they represent different processes. This is the result of different model purposes, but also reflects legacies in model code, modelers' preferences, and the 'prevailing spirit of the epoch'. The lack of firm theories, laws and 'first principles' in ecology provides high degrees of freedom in model development, but also results in high responsibilities for model developers and the need for rigorous model evaluation. Synthesis. The currently available model diversity is beneficial: convergence in simulations of structurally different models indicates robust projections, while convergence of similar models may convey a false sense of certainty. The existing model diversity-with the exception of global models-can be exploited for improved projections based on multiple models. We strongly recommend balanced further developments of forest models that should particularly focus on establishment and mortality processes, in order to provide robust information for decisions in ecosystem management and policymaking.

An evaluation of multi-species empirical tree mortality algorithms for dynamic vegetation modelling.

Tree mortality is key for projecting forest dynamics, but difficult to portray in dynamic vegetation models (DVMs). Empirical mortality algorithms (MAs) are often considered promising, but little is known about DVM robustness when employing MAs of various structures and origins for multiple species. We analysed empirical MAs for a suite of European tree species within a consistent DVM framework under present and future climates in two climatically different study areas in Switzerland and evaluated their performance using empirical data from old-growth forests across Europe. DVM projections under present climate showed substantial variations when using alternative empirical MAs for the same species. Under climate change, DVM projections showed partly contrasting mortality responses for the same species. These opposing patterns were associated with MA structures (i.e. explanatory variables) and occurred independent of species ecological characteristics. When comparing simulated forest structure with data from old-growth forests, we found frequent overestimations of basal area, which can lead to flawed projections of carbon sequestration and other ecosystem services. While using empirical MAs in DVMs may appear promising, our results emphasize the importance of selecting them cautiously. We therefore synthesize our insights into a guideline for the appropriate use of empirical MAs in DVM applications.

Tree recruitment is determined by stand structure and shade tolerance with uncertain role of climate and water relations.

Tree regeneration is a key process for long-term forest dynamics, determining changes in species composition and shaping successional trajectories. While tree regeneration is a highly stochastic process, tree regeneration studies often cover narrow environmental gradients only, focusing on specific forest types or species in distinct regions. Thus, the larger-scale effects of temperature, water availability, and stand structure on tree regeneration are poorly understood.We investigated these effects in respect of tree recruitment (in-growth) along wide environmental gradients using forest inventory data from Flanders (Belgium), northwestern Germany, and Switzerland covering more than 40 tree species. We employed generalized linear mixed models to capture the abundance of tree recruitment in response to basal area, stem density, shade casting ability of a forest stand as well as site-specific degree-day sum (temperature), water balance, and plant-available water holding capacity. We grouped tree species to facilitate comparisons between species with different levels of tolerance to shade and drought.Basal area and shade casting ability of the overstory had generally a negative impact on tree recruitment, but the effects differed between levels of shade tolerance of tree recruitment in all study regions. Recruitment rates of very shade-tolerant species were positively affected by shade casting ability. Stem density and summer warmth (degree-day sum) had similar effects on all tree species and successional strategies. Water-related variables revealed a high degree of uncertainty and did not allow for general conclusions. All variables had similar effects independent of the varying diameter thresholds for tree recruitment in the different data sets.Synthesis: Shade tolerance and stand structure are the main drivers of tree recruitment along wide environmental gradients in temperate forests. Higher temperature generally increases tree recruitment rates, but the role of water relations and drought tolerance remains uncertain for tree recruitment on cross-regional scales.

Grow slowly, persist, dominate-Explaining beech dominance in a primeval forest.

Being able to persist in deep shade is an important characteristic of juvenile trees, often leading to a strong dominance of shade-tolerant species in forests with low canopy turnover and a low disturbance rate. While leaf, growth, and storage traits are known to be key components of shade tolerance, their interplay during regeneration development and their influence on juveniles' survival time remains unclear. We assessed the ontogenetic effects of these three traits on the survival time of beech (Fagus sylvatica), and Norway and sycamore maples (Acer pseudoplatanus, Acer platanoides) in a primeval beech forest. Biomass allocation, age, and content of nonstructural carbohydrates (NSC) were measured in the stems and roots of 289 seedlings and saplings in high- and low-vitality classes. Saplings experienced a trade-off between absolute growth rate (AGR) and storage (NSC) as the leaf area ratio (LAR) decreases with biomass development. High LAR but low AGR and low NSC corresponded to beech with a marked ability to persist in deep shade while awaiting canopy release. In turn, a comparably small LAR in combination with a high AGR and higher storage (NSC), as observed in Norway maple and sycamore maple, reduced sapling survival time, thus offering an explanation for beech dominance and maple disappearance in the undergrowth of old-growth beech forests.

Growth resistance and resilience of mixed silver fir and Norway spruce forests in central Europe: Contrasting responses to mild and severe droughts.

Extreme droughts are expected to increase in frequency and severity in many regions of the world, threatening multiple ecosystem services provided by forests. Effective strategies to adapt forests to such droughts require comprehensive information on the effects and importance of the factors influencing forest resistance and resilience. We used a unique combination of inventory and dendrochronological data from a long-term (>30 years) silvicultural experiment in mixed silver fir and Norway spruce mountain forests along a temperature and precipitation gradient in southwestern Germany. We aimed at examining the mechanisms and forest stand characteristics underpinning the resistance and resilience to past mild and severe droughts. We found that (i) fir benefited from mild droughts and showed higher resistance (i.e., lower growth loss during drought) and resilience (i.e., faster return to pre-drought growth levels) than spruce to all droughts; (ii) species identity determined mild drought responses while species interactions and management-related factors strongly influenced the responses to severe droughts; (iii) intraspecific and interspecific interactions had contrasting effects on the two species, with spruce being less resistant to severe droughts when exposed to interaction with fir and beech; (iv) higher values of residual stand basal area following thinning were associated with lower resistance and resilience to severe droughts; and (v) larger trees were resilient to mild drought events but highly vulnerable to severe droughts. Our study provides an analytical approach for examining the effects of different factors on individual tree- and stand-level drought response. The forests investigated here were to a certain extent resilient to mild droughts, and even benefited from such conditions, but were strongly affected by severe droughts. Lastly, negative effects of severe droughts can be reduced through modifying species composition, tree size distribution and stand density in mixed silver fir-Norway spruce forests.

Tackling unresolved questions in forest ecology: The past and future role of simulation models.

Understanding the processes that shape forest functioning, structure, and diversity remains challenging, although data on forest systems are being collected at a rapid pace and across scales. Forest models have a long history in bridging data with ecological knowledge and can simulate forest dynamics over spatio-temporal scales unreachable by most empirical investigations.We describe the development that different forest modelling communities have followed to underpin the leverage that simulation models offer for advancing our understanding of forest ecosystems.Using three widely applied but contrasting approaches - species distribution models, individual-based forest models, and dynamic global vegetation models - as examples, we show how scientific and technical advances have led models to transgress their initial objectives and limitations. We provide an overview of recent model applications on current important ecological topics and pinpoint ten key questions that could, and should, be tackled with forest models in the next decade.Synthesis. This overview shows that forest models, due to their complementarity and mutual enrichment, represent an invaluable toolkit to address a wide range of fundamental and applied ecological questions, hence fostering a deeper understanding of forest dynamics in the context of global change.

Stand-scale climate change impacts on forests over large areas: transient responses and projection uncertainties.

The increasing impacts of climate change on forest ecosystems have triggered multiple model-based impact assessments for the future, which typically focused either on a small number of stand-scale case studies or on large scale analyses (i.e., continental to global). Therefore, substantial uncertainty remains regarding the local impacts over large areas (i.e., regions to countries), which is particularly problematic for forest management. We provide a comprehensive, high-resolution assessment of the climate change sensitivity of managed Swiss forests (~10,000 km2 ), which cover a wide range of environmental conditions. We used a dynamic vegetation model to project the development of typical forest stands derived from a stratification of the Third National Forest Inventory until the end of the 22nd century. Two types of simulations were conducted: one limited to using the extant local species, the other enabling immigration of potentially more climate-adapted species. Moreover, to assess the robustness of our projections, we quantified and decomposed the uncertainty in model projections resulting from the following sources: (1) climate change scenarios, (2) local site conditions, and (3) the dynamic vegetation model itself (i.e., represented by a set of model versions), an aspect hitherto rarely taken into account. The simulations showed substantial changes in basal area and species composition, with dissimilar sensitivity to climate change across and within elevation zones. Higher-elevation stands generally profited from increased temperature, but soil conditions strongly modulated this response. Low-elevation stands were increasingly subject to drought, with strong negative impacts on forest growth. Furthermore, current stand structure had a strong effect on the simulated response. The admixture of drought-tolerant species was found advisable across all elevations to mitigate future adverse climate-induced effects. The largest uncertainty in model projections was associated with climate change scenarios. Uncertainty induced by the model version was generally largest where overall simulated climate change impacts were small, thus corroborating the utility of the model for making projections into the future. Yet, the large influence of both site conditions and the model version on some of the projections indicates that uncertainty sources other than climate change scenarios need to be considered in climate change impact assessments.

How does varying water supply affect oxygen isotope variations in needles and tree rings of Scots pine?

In many regions, drought is suspected to be a cause of Scots pine decline and mortality, but the underlying physiological mechanisms remain unclear. Because of their relationship to ecohydrological processes, δ18O values in tree rings are potentially useful for deciphering long-term physiological responses and tree adaptation to increasing drought. We therefore analyzed both needle- and stem-level isotope fractionations in mature trees exposed to varying water supply. In a first experiment, we investigated seasonal δ18O variations in soil and needle water of Scots pine in a dry inner Alpine valley in Switzerland, comparing drought-stressed trees with trees that were irrigated for more than 10 years. In a second experiment, we analyzed twentieth-century δ18O variations in tree rings of the same forest, including a group of trees that had recently died. We observed less 18O enrichment in needle water of drought-stressed compared with irrigated trees. We applied different isotope fractionation models to explain these results, including the Péclet and the two-pool correction, which considers the ratio of unenriched xylem water in the needles to total needle water. Based on anatomical measurements, we found this ratio to be unchanged in drought-stressed needles, although they were shorter. The observed lower 18O enrichment in needles of stressed trees was therefore likely caused by increased effective path length for water movement within the leaf lamina. In the tree-ring study, we observed lower δ18O values in tree rings of dead trees compared with survivors during several decades prior to their death. These lower values in declining trees are consistent with the lower needle water 18O enrichment observed for drought-stressed compared with irrigated trees, suggesting that this needle-level signal is reflected in the tree rings, although changes in rooting depth could also play a role. Our study demonstrates that long-term effects of drought are reflected in the tree-ring δ18O values, which helps to provide a better understanding of past tree physiological changes of Scots pine.

Assessing the response of forest productivity to climate extremes in Switzerland using model-data fusion.

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long-term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3-PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960-2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha-1  year-1  km-1 for P. abies and 0.93 ± 0.010 Mg C ha-1  year-1  km-1 for F. sylvatica). During warm-dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm-dry extremes. Importantly, cold-dry extremes had negative impacts on regional forest NPP comparable to warm-dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.

Bayesian calibration of a growth-dependent tree mortality model to simulate the dynamics of European temperate forests.

Dynamic vegetation models (DVMs) are important tools to understand and predict the functioning and dynamics of terrestrial ecosystems under changing environmental conditions. In these models, uncertainty in the description of demographic processes, in particular tree mortality, is a persistent problem. Current mortality formulations lack realism and are insufficiently constrained by empirical evidence. It has been suggested that empirically estimated mortality submodels would enhance DVM performance, but due to the many processes and interactions within a DVM, the claim has rarely been tested. Here, we compare the performance of three alternative growth-dependent tree mortality submodels in the DVM ForClim: (1) a mortality function with theoretical foundation (ForClim v3.3); (2) a mortality function with parameters directly estimated based on forest inventory data; and (3) the same function, but with parameters estimated using an inverse approach through Bayesian calibration (BC). Time series of inventory data from 30 ecologically distinct Swiss natural forest reserves collected over 35+ yr, including the main tree species of Central Europe, were used for the calibration and subsequent validation of the mortality functions and the DVM. The recalibration resulted in mortality parameters that differed from the direct empirical estimates, particularly for the relationship between tree size and mortality. The calibrated parameters outperformed the direct estimates, and to a lesser extent the original mortality function, for predicting decadal-scale forest dynamics at both calibration and validation sites. The same pattern was observed regarding the plausibility of their long-term projections under contrasting environmental conditions. Our results demonstrate that inverse calibration may be useful even when direct empirical estimates of DVM parameters are available, as structural model deficiencies or data problems can result in discrepancies between direct and inverse estimates. Thus, we interpret the good performance of the inversely calibrated model for long-term projections (which were not a calibration target) as evidence that the calibration did not compensate for model errors. Rather, we surmise that the discrepancy was mainly caused by a lack of representativeness of the mortality data. Our results underline the potential for learning more about elusive processes, such as tree mortality or recruitment, through data integration in DVMs.

Early emergence increases survival of tree seedlings in Central European temperate forests despite severe late frost.

Global warming is expected to result in earlier emergence of tree seedlings that may experience higher damages and mortality due to late frost in spring. We monitored emergence, characteristics, and survival of seedlings across ten tree species in temperate mixed deciduous forests of Central Europe over one and a half year. We tested whether the timing of emergence represents a trade-off for seedling survival between minimizing frost risk and maximizing the length of the growing period. Almost two-thirds of the seedlings died during the first growing period. The timing of emergence was decisive for seedling survival. Although seedlings that emerged early faced a severe late frost event, they benefited from a longer growing period resulting in increased overall survival. Larger seedling height and higher number of leaves positively influenced survival. Seedlings growing on moss had higher survival compared to mineral soil, litter, or herbaceous vegetation. Synthesis. Our findings demonstrate the importance of emergence time for survival of tree seedlings, with early-emerging seedlings more likely surviving the first growing period.

Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale.

Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10-40% per century under current climate and 20-170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics.

Climate-induced shifts in leaf unfolding and frost risk of European trees and shrubs.

Climate warming has advanced leaf unfolding of trees and shrubs, thus extending the growing period but potentially exposing plants to increased frost risk. The relative shifts in the timing of leaf unfolding vs. the timing and intensity of frost events determine whether frost risk changes under climate warming. Here we test whether the frost risk for unfolding leaves of 13 European tree and shrub species has changed over more than 60 years using dynamic state-space models and phenological observations from 264 sites located between 200 and 1900 m a.s.l. across Switzerland. Trees and shrubs currently feature sufficient safety margins regarding frost risk, which increase from early- to late-leafing species and tend to decrease with increasing elevation. Particularly after 1970 to 1990 and at higher elevations, leaf unfolding has advanced across all species. While the time between the last critical frost and leaf unfolding has shifted from predominantly positive trends in the late 1950s and 1960s to a trend reversal since the 2000s, the minimum temperature during leaf unfolding has mostly increased since the 1980s. These dynamic shifts in leaf unfolding and frost risk demonstrate species- and site-specific responses of trees and shrubs to climate cooling and warming.

Long-term response of forest productivity to climate change is mostly driven by change in tree species composition.

Climate change affects ecosystem functioning directly through impacts on plant physiology, resulting in changes of global productivity. However, climate change has also an indirect impact on ecosystems, through changes in the composition and diversity of plant communities. The relative importance of these direct and indirect effects has not been evaluated within a same generic approach yet. Here we took advantage of a novel approach for disentangling these two effects in European temperate forests across a large climatic gradient, through a large simulation-based study using a forest succession model. We first showed that if productivity positively correlates with realized tree species richness under a changed climate, indirect effects appear pivotal to understand the magnitude of climate change impacts on forest productivity. We further detailed how warmer and drier conditions may affect the diversity-productivity relationships (DPRs) of temperate forests in the long term, mostly through effects on species recruitment, ultimately enhancing or preventing complementarity in resource use. Furthermore, losing key species reduced the strength of DPRs more severely in environments that are becoming climatically harsher. By disentangling direct and indirect effects of climate change on ecosystem functioning, these findings explain why high-diversity forests are expected to be more resilient to climate change.