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Abstract

This study aimed to simulate oak and beech forest growth under various scenarios of climate change and to evaluate how the forest response depends on site properties and particularly on stand characteristics using the individual process-based model HETEROFOR. First, this model was evaluated on a wide range of site conditions. We used data from 36 long-term forest monitoring plots to initialize, calibrate, and evaluate HETEROFOR. This evaluation showed that HETEROFOR predicts individual tree radial growth and height increment reasonably well under different growing conditions when evaluated on independent sites. In our simulations under constant CO2 concentration ([CO2]cst) for the 2071-2100 period, climate change induced a moderate net primary production (NPP) gain in continental and mountainous zones and no change in the oceanic zone. The NPP changes were negatively affected by air temperature during the vegetation period and by the annual rainfall decrease. To a lower extent, they were influenced by soil extractable water reserve and stand characteristics. These NPP changes were positively affected by longer vegetation periods and negatively by drought for beech and larger autotrophic respiration costs for oak. For both species, the NPP gain was much larger with rising CO2 concentration ([CO2]var) mainly due to the CO2 fertilisation effect. Even if the species composition and structure had a limited influence on the forest response to climate change, they explained a large part of the NPP variability (44% and 34% for [CO2]cst and [CO2]var, respectively) compared to the climate change scenario (5% and 29%) and the inter-annual climate variability (20% and 16%). This gives the forester the possibility to act on the productivity of broadleaved forests and prepare them for possible adverse effects of climate change by reinforcing their resilience.

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... Drought induced an increase in oxidative pressure from the transcript level [68]. Under a constant CO2 concentration, the net primary production was positively affected by longer vegetation periods and negatively by respiration costs in European oak trees [69]. In the Mediterranean region, climate change induces heat waves and droughts, disturbing forest species and affecting productivity. ...
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Oaks exhibit unique biological characteristics and high adaptability to complex climatic and soil conditions. They are widely distributed across various regions, spanning 40 degrees latitude and 75 degrees longitude. The total area of oak forest in China is 16.72 million hm2. There are 60 lineages of Quercus in China, including 49 species, seven varieties, and four subgenera. Archaeological data indicate that oaks were already widely distributed in ancient times, and they are dominant trees in vast regions of China’s forests. In addition, the acorn was an important food for ancestral humans, and it has accompanied human civilization since the early Paleolithic. Diverse oak species are widely distributed and have great functional value, such as for greening, carbon sequestration, industrial and medicinal uses, and insect rearing. Long-term deforestation, fire, diseases, and pests have led to a continuous decline in oak resources. This study discusses the Quercus species and their distribution in China, ecological adaptation, and the threats facing the propagation and growth of oaks in a changing world. This will give us a better understanding of Quercus resources, and provide guidance on how to protect and better utilize germplasm resources in China. The breeding of new varieties, pest control, and chemical and molecular research also need to be strengthened in future studies.
... Height growth was predicted less accurately than BAI and was underestimated for both conifers and broadleaved species (negative bias of 31.7% and 33.3%), particularly for trees with the highest height increment. This lower accuracy in height predictions is common in forest growth models (Schwalm and Ek, 2004;de Wergifosse et al., 2022;Korol et al., 1995;Strimbu et al., 2017), notably due to the higher potential measurement errors than for diameter. These inaccuracies in height measurements, which can be estimated within 1m (Jurjević et al., 2020), are present during both initial and final inventories 405 and have a greater impact on predictions in areas like Québec where tree height growth is limited. ...
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Process-based forest growth models with spatially explicit representation are a relevant tool to investigate innovative silviculture practices and/or climate change effects because they are based on key ecophysiological processes and account for the effects of local competition for resources on tree growth. Such models are rare, often calibrated for a very limited number of species and rarely in mixed and/or uneven-aged stands, and none are suitable for the temperate forests of Québec. The aim of this study was to calibrate and evaluate HETEROFOR, a process-based and spatially explicit model based on resource sharing, for 23 functionally diverse tree species in forest stands with contrasting species compositions and environmental conditions in southern Québec. Using data from the forest inventory of Québec, we evaluated the ability of HETEROFOR to predict the short-term growth (5–16 years) of these species at the tree and stand levels, and the long-term dynamics (120 years) of red and sugar maple stands. The comparison between the prediction quality for the calibration and evaluation datasets showed the robustness of the model performance in predicting individual tree growth. The model reproduced correctly individual basal area increment (BAI) of the validation dataset with a mean Pearson’s correlation coefficient of 0.56 and a mean bias of 18 %. Our results also highlighted that considering tree position is of importance for predicting individual tree growth most accurately in complex stands with both vertical and horizontal heterogeneous structure. The model also showed a good ability to reproduce BAI at the stand level, both for monospecific (bias of -3.7 %, Pearson’s r = 0.55) and multi-species stands (bias of -9.1 %, Pearson’s r = 0.62). Long-term simulations of red maple and sugar maple showed that HETEROFOR was able to accurately predict the growth (basal area and height) and mortality processes from the seedling stage to the mature stand. Our results suggest that HETEROFOR is a reliable option to simulate forest growth in southern Québec and test new forestry practices under future climate scenarios.
... Mechanistic models are often regarded as having a larger degree of uncertainty than empirical models -due to their larger number of parameters (Adams et al., 2013), but mechanistic models of vegetation dynamics can achieve good performance when calibrated for specific stands and parameter estimates are carefully chosen for target species (de Wergifosse et al., 2022;Forrester et al., 2021). In the case of mechanistic trait-enabled models, one can expect substantial biases with respect to the prediction forest dynamics because key parameters of demographic processes are unlikely to be matched by observable database traits. ...
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Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity, which requires moving away from broadly-defined functional types. Different approaches have been adopted in the last years to incorporate a trait-based perspective into modeling exercises. A common parametrization strategy involves using trait data to represent functional variation between individuals while discard taxonomic identity, but this strategy ignores the phylogenetic signal of trait variation and cannot be employed when predictions for specific taxa are needed, as in applications to inform forest management planning. An alternative strategy involves adapting the taxonomic resolution of model entities to that of the data source employed for large-scale initialization and estimating functional parameters from available plant trait databases while adopting alternative solutions for missing data and non-observable parameters. Here we report the advantages and limitations of this second strategy according to our experience in the development of MEDFATE (v. 2.8.1), a novel cohort-based and trait-enabled model of forest dynamics, for its application over a region in the Western Mediterranean Basin. First, 217 taxonomic entities were defined according to woody species codes of the Spanish National Forest Inventory. While forest inventory data were used to obtain some empirical parameter estimates, a large proportion of physiological, morphological, and anatomical parameters were mapped to measured plant traits, with estimates extracted from multiple databases and averaged at the required taxonomic level. Estimates for non-observable key parameters were obtained using meta-modeling and calibration exercises. Missing values were filled using imputation procedures based on trait coordination, taxonomic averages or both. The model properly simulated observed historical basal area changes, with a performance similar to an empirical model trained for the same region. While strong efforts are still required to parameterize trait-enabled models for multiple taxa, estimation procedures can be progressively refined, transferred to other regions or models and iterated following data source changes by employing automated workflows. We advocate for the adoption of trait-enabled population-structured models for regional-level projections of forest function and dynamics.
... Our model results highlight, for Central and Northern temperate and boreal European forests, the importance of forest structure to sustain or even enhance productivity and carbon storage. This in turn indicates that management practices may be quantitatively as important as future climate and atmospheric CO 2 concentration in regulating the carbon sink strength of forests, which is in line with some previous modeling studies ( Garcia-Gonzalo et al., 2007;Akujärvi et al., 2019;de Wergifosse et al., 2022). These simulations indicate that silvicultural practices included in the model would persist as key factors in the regulation of carbon sequestration through the end of this century under any of the CMIP5 RCP scenarios. ...
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Forest management practices might act as nature-based methods to remove CO2 from the atmosphere and slow anthropogenic climate change and thus support an EU forest-based climate change mitigation strategy. However, the extent to which diversified management actions could lead to quantitatively important changes in carbon sequestration and stocking capacity at the tree level remains to be thoroughly assessed. To that end, we used a state-of-the-science bio-geochemically based forest growth model to simulate effects of multiple forest management scenarios on net primary productivity (NPP) and potential carbon woody stocks (pCWS) under twenty scenarios of climate change in a suite of observed and virtual forest stands in temperate and boreal European forests. Previous modelling experiments indicated that the capacity of forests to assimilate and store atmospheric CO2 in woody biomass is already being attained under business-as-usual forest management practices across a range of climate change scenarios. Nevertheless, we find that on the long-term, with increasing atmospheric CO2 concentration and warming, managed forests show both higher productivity capacity and a larger potential pool size of stored carbon than unmanaged forests as long as thinning and tree harvesting are of moderate intensity.
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Process-based vegetation models are widely used to predict local and global ecosystem dynamics and climate change impacts. Due to their complexity, they require careful parameterization and evaluation to ensure that projections are accurate and reliable. The PROFOUND Database (PROFOUND DB) provides a wide range of empirical data on European forests to calibrate and evaluate vegetation models that simulate climate impacts at the forest stand scale. A particular advantage of this database is its wide coverage of multiple data sources at different hierarchical and temporal scales, together with environmental driving data as well as the latest climate scenarios. Specifically, the PROFOUND DB provides general site descriptions, soil, climate, CO2, nitrogen deposition, tree and forest stand level, and remote sensing data for nine contrasting forest stands distributed across Europe. Moreover, for a subset of five sites, time series of carbon fluxes, atmospheric heat conduction and soil water are also available. The climate and nitrogen deposition data contain several datasets for the historic period and a wide range of future climate change scenarios following the Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, RCP8.5). We also provide pre-industrial climate simulations that allow for model runs aimed at disentangling the contribution of climate change to observed forest productivity changes. The PROFOUND DB is available freely as a “SQLite” relational database or “ASCII” flat file version (at https://doi.org/10.5880/PIK.2020.006/; Reyer et al., 2020). The data policies of the individual contributing datasets are provided in the metadata of each data file. The PROFOUND DB can also be accessed via the ProfoundData R package (https://CRAN.R-project.org/package=ProfoundData; Silveyra Gonzalez et al., 2020), which provides basic functions to explore, plot and extract the data for model set-up, calibration and evaluation.
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A central challenge in global change research is the projection of the future behavior of a system based upon past observations. Tree‐ring data have been used increasingly over the last decade to project tree growth and forest ecosystem vulnerability under future climate conditions. But how can the response of tree growth to past climate variation predict the future, when the future does not look like the past? Space‐for‐time substitution (SFTS) is one way to overcome the problem of extrapolation: the response at a given location in a warmer future is assumed to follow the response at a warmer location today. Here we evaluated an SFTS approach to projecting future growth of Douglas‐fir (Pseudotsuga menziesii ), a species that occupies an exceptionally large environmental space in North America. We fit a hierarchical mixed‐effects model to capture ring‐width variability in response to spatial and temporal variation in climate. We found opposing gradients for productivity and climate sensitivity with highest growth rates and weakest response to interannual climate variation in the mesic coastal part of Douglas‐fir’s range; narrower rings and stronger climate sensitivity occurred across the semi‐arid interior. Ring‐width response to spatial vs. temporal temperature variation was opposite in sign, suggesting that spatial variation in productivity, caused by local adaptation and other slow processes, cannot be used to anticipate changes in productivity caused by rapid climate change. We thus substituted only climate sensitivities when projecting future tree growth. Growth declines were projected across much of Douglas‐fir’s distribution, with largest relative decreases in the semiarid U.S. Interior West and smallest in the mesic Pacific Northwest. We further highlight the strengths of mixed‐effects modeling for reviving a conceptual cornerstone of dendroecology, Cook’s 1987 aggregate growth model, and the great potential to use tree‐ring networks and results as a calibration target for next‐generation vegetation models.
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Within the Copernicus Climate Change Service (C3S), ECMWF is producing the ERA5 reanalysis, which embodies a detailed record of the global atmosphere, land surface and ocean waves from 1950 onwards once completed. This new reanalysis replaces the ERA‐Interim reanalysis that was started in 2006 (spanning 1979 onwards). ERA5 is based on the Integrated Forecasting System (IFS) Cy41r2 which was operational in 2016. ERA5 thus benefits from a decade of developments in model physics, core dynamics and data assimilation. In addition to a significantly enhanced horizontal resolution of 31 km, compared to 80 km for ERA‐Interim, ERA5 has hourly output throughout, and an uncertainty estimate from an ensemble (3‐hourly at half the horizontal resolution). This paper describes the general setup of ERA5, as well as a basic evaluation of characteristics and performance. Focus is on the dataset from 1979 onwards that is currently publicly available. Re‐forecasts from ERA5 analyses show a gain of up to one day in skill with respect to ERA‐Interim. Comparison with radiosonde and PILOT data prior to assimilation shows an improved fit for temperature, wind and humidity in the troposphere, but not the stratosphere. A comparison with independent buoy data shows a much improved fit for ocean wave height. The uncertainty estimate reflects the evolution of the observing systems used in ERA5. The enhanced temporal and spatial resolution allows for a detailed evolution of weather systems. For precipitation, global‐mean correlation with monthly‐mean GPCP data is increased from 67% to 77%. In general low‐frequency variability is found to be well‐represented and from 10 hPa downwards general patterns of anomalies in temperature match those from the ERA‐Interim, MERRA‐2 and JRA‐55 reanalyses. This article is protected by copyright. All rights reserved.
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Late-spring frosts (LSFs) affect the performance of plants and animals across the world's temperate and boreal zones, but despite their ecological and economic impact on agriculture and forestry, the geographic distribution and evolutionary impact of these frost events are poorly understood. Here, we analyze LSFs between 1959 and 2017 and the resistance strategies of Northern Hemisphere woody species to infer trees' adaptations for minimizing frost damage to their leaves and to forecast forest vulnerability under the ongoing changes in frost frequencies. Trait values on leaf-out and leaf-freezing resistance come from up to 1,500 temperate and boreal woody species cultivated in common gardens. We find that areas in which LSFs are common, such as eastern North America, harbor tree species with cautious (late-leafing) leaf-out strategies. Areas in which LSFs used to be unlikely, such as broad-leaved forests and shrublands in Europe and Asia, instead harbor opportunistic tree species (quickly reacting to warming air temperatures). LSFs in the latter regions are currently increasing, and given species' innate resistance strategies, we estimate that ∼35% of the European and ∼26% of the Asian temperate forest area, but only ∼10% of the North American, will experience increasing late-frost damage in the future. Our findings reveal region-specific changes in the spring-frost risk that can inform decision-making in land management, forestry, agriculture, and insurance policy.
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Climate warming is currently advancing spring leaf‐out of temperate and boreal trees, enhancing net primary productivity (NPP) of forests. However, it remains unclear whether this trend will continue, preventing for accurate projections of ecosystem functioning and climate feedbacks. Several ecophysiological mechanisms have been proposed to regulate the timing of leaf emergence in response to changing environmental cues, but the relative importance of those mechanisms remains unclear. Here, we use 727,401 direct phenological observations of common European forest trees to examine the dominant controls on leaf‐out. Using the emerging mechanisms, we forecast future trajectories of spring arrival and evaluate the consequences for forest carbon dynamics. By representing hypothesized relationships with autumn temperature, winter chilling, and the timing of spring onset, we accurately predicted reductions in the advance of leaf‐out. There was a strong consensus between our empirical model and existing process‐based models, revealing that the advance in leaf‐out will not exceed 2 weeks over the rest of the century. We further estimate that, under a ‘business‐as‐usual’ climate scenario, earlier spring arrival will enhance NPP of temperate and boreal forests by ~0.2 Gt per year at the end of the century. In contrast, previous estimates based on a simple degree‐day model range around 0.8 Gt. As such, the expected NPP is drastically reduced in our updated model relative to previous estimates—by a total of ~25 Gt over the rest of the century. These findings reveal important environmental constraints on the productivity of broad‐leaved deciduous trees and highlight that shifting spring phenology is unlikely to slow the rate of warming by offsetting anthropogenic carbon emissions.
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Climate change affects forest growth in numerous and sometimes opposite ways and the resulting trend is often difficult to predict for a given site. Integrating and structuring the knowledge gained from the monitoring and experimental studies into process-based models is an interesting approach to predict the response of forest ecosystems to climate change. While the first generation of such models operates at stand level, we need now individual-based and spatially-explicit approaches in order to account for structurally complex stands whose importance is increasingly recognized in the changing environment context. Among the climate-sensitive drivers of forest growth, phenology and water availability are often cited as crucial elements. They influence, for example, the length of the vegetation period during which photosynthesis takes place and the stomata opening, which determines the photosynthesis rate. In this paper, we describe the phenology and water balance modules integrated in the tree growth model HETEROFOR and evaluate them on six Belgian sites. More precisely, we assess the ability of the model to reproduce key phenological processes (budburst, leaf development, yellowing and fall) as well as water fluxes. Three variants are used to predict budburst (Uniforc, Unichill and Sequential), which differ regarding the inclusion of chilling and/or forcing periods and the calculation of the coldness or heat accumulation. Among the three, the Sequential approach is the least biased (overestimation of 2.46 days) while Uniforc (chilling not considered) best accounts for the interannual variability (Pearson’s R = 0.68). For the leaf development, yellowing and fall, predictions and observation are in accordance. Regarding the water balance module, the predicted throughfall is also in close agreement with the measurements (Pearson’s R = 0.856, bias = −1.3 %) and the soil water dynamics across the year is well-reproduced for all the study sites (Pearson’s R comprised between 0.893 and 0.950, and bias between −1.81 and −9.33 %). The positive results from the model assessment will allow us to use it reliably in projection studies to evaluate the impact of climate change on tree growth and test how diverse forestry practices can adapt forests to these changes.
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Given the multiple abiotic and biotic stressors resulting from global changes, management systems and practices must be adapted in order to maintain and reinforce the resilience of forests. Among others, the transformation of monocultures into uneven-aged and mixed stands is an avenue to improve forest resilience. To explore the forest response to these new silvicultural practices under a changing environment, one need models combining a process-based approach with a detailed spatial representation, which is very rare. We therefore decided to develop our own model (HETEROFOR) according to a spatially explicit approach describing individual tree growth based on resource sharing (light, water and nutrients). HETEROFOR was progressively elaborated through the integration of various modules (light interception, phenology, water cycling, photosynthesis and respiration, carbon allocation, mineral nutrition and nutrient cycling) within CAPSIS, a collaborative modelling platform devoted to tree growth and stand dynamics. The advantage of using such a platform is to use common development environment, model execution system, user- interface and visualization tools and to share data structures, objects, methods and libraries. This paper describes the carbon-related processes of HETEROFOR (photosynthesis, respiration, carbon allocation and tree dimensional growth) and evaluates the model performances for a mixed oak and beech stand in Wallonia (Belgium). This first evaluation showed that HETEROFOR predicts well individual radial growth and is able to reproduce size-growth relationships. We also noticed that the more empirical options for describing maintenance respiration and crown extension provide the best results while the process-based approach best performs for photosynthesis. To illustrate how the model can be used to predict climate change impacts on forest ecosystems, the growth dynamics in this stand was simulated according to four IPCC climate scenarios. According to these simulations, the tree growth trends will be governed by the CO2 fertilization effect with the increase in vegetation period length and in water stress also playing a role but offsetting each other.
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Gross primary production (GPP) is partitioned to autotrophic respiration (Ra) and net primary production (NPP), the latter being used to build plant tissues and synthesize non-structural and secondary compounds. Waring et al. (1998) suggested that a NPP:GPP ratio of 0.47 ± 0.04 (s.d.) is universal across biomes, tree species and stand ages. Representing NPP in models as a fixed fraction of GPP, they argued, would be both simpler and more accurate than trying to simulate Ra mechanistically. This paper reviews progress in understanding the NPP:GPP ratio in forests during the 20 years since Waring et al.. Research has confirmed the existence of pervasive acclimation mechanisms that tend to stabilize the NPP:GPP ratio, and indicates that Ra should not be modelled independently of GPP. Nonetheless, studies indicate that the value of this ratio is influenced by environmental factors, stand age and management. The average NPP:GPP ratio in over 200 studies, representing different biomes, species and forest stand ages, was found to be 0.46, consistent with the central value that Waring et al. proposed but with a much larger standard deviation (± 0.12) and a total range (0.22 to 0.79) that is too large to be disregarded.
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Human societies depend on an Earth system that operates within a constrained range of nutrient availability, yet the recent trajectory of terrestrial nitrogen (N) availability is uncertain. Examining patterns of foliar N concentrations and isotope ratios (δ15N) from more than 43,000 samples acquired over 37 years, here we show that foliar N concentration declined by 9% and foliar δ15N declined by 0.6–1.6‰. Examining patterns across different climate spaces, foliar δ15N declined across the entire range of mean annual temperature and mean annual precipitation tested. These results suggest declines in N supply relative to plant demand at the global scale. In all, there are now multiple lines of evidence of declining N availability in many unfertilized terrestrial ecosystems, including declines in δ15N of tree rings and leaves from herbarium samples over the past 75–150 years. These patterns are consistent with the proposed consequences of elevated atmospheric carbon dioxide and longer growing seasons. These declines will limit future terrestrial carbon uptake and increase nutritional stress for herbivores.
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The Paris Agreement advances forest management as one of the pathways to halt climate warming through carbon dioxide (CO2) emission reduction1. The climate benefits from carbon sequestration from forest management may, however, be reinforced, counteracted, or even offset by concurrent management-induced changes in surface albedo, surface roughness, biogenic volatile organic compound emissions, transpiration, and sensible heat flux2–4. Forest management could, thus, offset CO2 emissions without halting global temperature rise. It remains, therefore, to be confirmed that sustainable forest management portfolios for the end of the 21st-century for Europe would comply with the Paris Agreement, i.e., reduce the growth rate of atmospheric CO2, reduce the radiative imbalance at the top of the atmosphere, and neither increase the near-surface air temperature nor decrease precipitation. Here we show that a spatially-optimized portfolio that maximises the carbon sink through carbon sequestration, wood use and product and energy substitution, reduces the growth rate of atmospheric CO2 but does not meet any of the other criteria. The portfolios that maximise the carbon sink or forest albedo pass only one, albeit different, criterion. Managing the European forests with the objective to reduce near-surface air temperature, on the other hand, will also reduce the atmospheric CO2 growth rate, thus meeting two out of four criteria. Our results demonstrate that if present-day forest cover is sustained, the additional climate benefits through forest management would be modest and local rather than global. Based on these findings we argue that if adaptation would require large-scale changes in species composition and silvicultural systems over Europe5,6, these changes could be implemented with little unintended climate effects.
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Abstract Background Forest management decisions are based on expectations of future developments. For sound decisions it is essential to accurately predict the expected values in future developments and to account for their inherent uncertainty, for example the impact of climate change on forests. Changing climatic conditions affect forest productivity and alter the risk profile of forests and forest enterprises. Intensifying drought stress is seen as one major risk factor threatening forest management in the north German lowlands. Drought stress reduces tree growth and vitality and might even trigger mortality. But so far, it is not possible to quantify effects of a persistent dryer climate on forest productivity at a level suitable for forest management. Methods We apply a well-established single-tree forest growth simulator to quantify the effect of persistent dryer climates on future forest productivity. We analyse the growth of Scots pine (Pinus sylvestris L.), European beech (Fagus sylvatica L.) and oak (Quercus robur L. and Quercus petraea (Matt.) Liebl.) in two forest regions in the north German lowlands for a time interval of 60 years until 2070. The growth response under three different climate projections is compared to a baseline scenario. Results The results show clear differences in volume increment to persistent dryer climates between tree species. The findings exhibit regional differences and temporal trends. While mean annual increment at biological rotation age of Scots pine and oak predominantly benefits from the projected climate conditions until 2070, beech might suffer losses of up to 3 m3·ha–1·yr–1 depending on climate scenario and region. However, in the projection period 2051 to 2070 the uncertainty ranges comprise positive as well as negative climatic effects for all species. Conclusions The projected changes in forest growth serve as quantitative contributions to provide decision support in the evaluation of, for example, species future site suitability and timber supply assessments. The analysis of productivity changes under persistent dryer climate complements the drought vulnerability assessment which is applied in practical forestry in northwestern Germany today. The projected species’ productivity has strong implications for forest management and the inherent uncertainty needs to be accounted for.
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Plants influence the atmosphere through fluxes of carbon, water and energy1, and can intensify drought through land-atmosphere feedback effects2-4. The diversity of plant functional traits in forests, especially physiological traits related to water (hydraulic) transport, may have a critical role in land-atmosphere feedback, particularly during drought. Here we combine 352 site-years of eddy covariance measurements from 40 forest sites, remote-sensing observations of plant water content and plant functional-trait data to test whether the diversity in plant traits affects the response of the ecosystem to drought. We find evidence that higher hydraulic diversity buffers variation in ecosystem flux during dry periods across temperate and boreal forests. Hydraulic traits were the predominant significant predictors of cross-site patterns in drought response. By contrast, standard leaf and wood traits, such as specific leaf area and wood density, had little explanatory power. Our results demonstrate that diversity in the hydraulic traits of trees mediates ecosystem resilience to drought and is likely to have an important role in future ecosystem-atmosphere feedback effects in a changing climate.
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Forest carbon use efficiency (CUE, the ratio of net to gross primary productivity) represents the fraction of photosynthesis that is not used for plant respiration. Although important, it is often neglected in climate change impact analyses. Here, we assess the potential impact of thinning on projected carbon-cycle dynamics and implications for forest CUE and its components (i.e. gross and net primary productivity and plant respiration), as well as on forest biomass production. Using a detailed process-based forest-ecosystem-model forced by climate outputs of five Earth System Models under four Representative- climate scenarios, we investigate the sensitivity of the projected future changes in the autotrophic carbon budget of three representative European forests. We focus on changes in CUE and carbon stocks as a result of warming, rising atmospheric CO 2 concentration and forest thinning. Results show that autotrophic carbon sequestration decreases with forest development and the decrease is faster with warming and in unthinned forests. This suggests that the combined impacts of climate change and changing CO2 concentrations, lead the forests to grow faster mature earlier but also die younger. In addition, we show that under future climate conditions, forest thinning could mitigate the decrease in CUE, increase carbon allocation into more recalcitrant woody-pools and reduce physiological-climate-induced mortality risks. Altogether, our results show that thinning can improve the efficacy of forest-based mitigation strategies and should be carefully considered within a portfolio of mitigation options.
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We investigate European regional climate change for time periods when the global mean temperature has increased by 1.5 and 2 °C compared to pre-industrial conditions. Results are based on regional downscaling of transient climate change simulations for the 21st century with global climate models (GCMs) from the fifth-phase Coupled Model Intercomparison Project (CMIP5). We use an ensemble of EURO-CORDEX high-resolution regional climate model (RCM) simulations undertaken at a computational grid of 12.5 km horizontal resolution covering Europe. The ensemble consists of a range of RCMs that have been used for downscaling different GCMs under the RCP8.5 forcing scenario. The results indicate considerable near-surface warming already at the lower 1.5 °C of warming. Regional warming exceeds that of the global mean in most parts of Europe, being the strongest in the northernmost parts of Europe in winter and in the southernmost parts of Europe together with parts of Scandinavia in summer. Changes in precipitation, which are less robust than the ones in temperature, include increases in the north and decreases in the south with a borderline that migrates from a northerly position in summer to a southerly one in winter. Some of these changes are already seen at 1.5 °C of warming but are larger and more robust at 2 °C. Changes in near-surface wind speed are associated with a large spread among individual ensemble members at both warming levels. Relatively large areas over the North Atlantic and some parts of the continent show decreasing wind speed while some ocean areas in the far north show increasing wind speed. The changes in temperature, precipitation and wind speed are shown to be modified by changes in mean sea level pressure, indicating a strong relationship with the large-scale circulation and its internal variability on decade-long timescales. By comparing to a larger ensemble of CMIP5 GCMs we find that the RCMs can alter the results, leading either to attenuation or amplification of the climate change signal in the underlying GCMs. We find that the RCMs tend to produce less warming and more precipitation (or less drying) in many areas in both winter and summer.
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Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die-off events have severe consequences for ecosystem services, biophysical and biogeochemical land–atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global monitoring network of forest mortality. In light of recent and anticipated large forest die-off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought-induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.
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We investigate European regional climate change for time periods when the global mean temperature has increased by respectively 1.5 °C and 2 °C compared to preindustrial conditions. Results are based on regional downscaling of transient climate change simulations for the 21st century with global climate models (GCMs) from the fifth phase Coupled Model Intercomparison Project (CMIP5). We use an ensemble of EURO-CORDEX high-resolution regional climate model (RCM) simulations undertaken at a computational grid of 12.5 km horizontal resolution covering Europe. The ensemble consists of a range of RCMs that have been used for downscaling different GCMs under different forcing scenarios. The results indicate considerable near-surface warming already at the lower 1.5 °C warming. Regional warming exceeds that of the global mean in most parts of Europe, strongest in northernmost parts of Europe in winter and in southernmost parts of Europe together with parts of Scandinavia in summer. Changes in precipitation, that are less robust than the ones in temperature, include increases in the north and decreases in the south with a borderline that migrates from a northerly position in summer to a southerly one in winter. Some of these changes are seen already at 1.5 °C warming but larger and more robust at 2 °C. Changes in near-surface wind speed are associated with a large spread between individual ensemble members at both warming levels. Relatively large areas over the North Atlantic and some parts of the continent shows decreasing wind speed while some ocean areas in the far north show increasing wind speed. The changes in temperature, precipitation and wind speed are shown to be modified by changes in mean sea level pressure indicating a strong relationship with the large-scale circulation and its internal variability on decade-long timescales. By comparing to a larger ensemble of CMIP5 GCMs we find that the RCMs can alter the results leading either to attenuation of amplification of the climate change signal in the underlying GCMs. We find that the RCMs tend to produce less warming and more precipitation (or less drying) in many areas in both winter and summer.
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Forest conservation strategies and plans can be unsuccessful if the new habitat conditions determined by climate change are not considered. Our work aims at investigating the likelihood of future suitability, distribution and diversity for some common European forest species under the projected changes in climate, focusing on Southern Europe. We combine an Ensemble Platform for Species Distribution Models (SDMs) to five Global Circulation Models (GCMs) driven by two Representative Concentration Pathways (RCPs), to produce maps of future climate-driven habitat suitability for ten categories of forest species and two time horizons. For each forest category and time horizon, ten maps of future distribution (5 GCMs by 2 RCPs) are thus combined in a single suitability map supplied with information about the “likelihood” adopting the IPCC terminology based on consensus among projections. Then, the statistical significance of spatially aggregated changes in forest composition at local and regional level is analyzed. Finally, we discuss the importance, among SDMs, that environmental predictors seem to have in influencing forest distribution. Future impacts of climate change appear to be diversified across forest categories. A strong change in forest regional distribution and local diversity is projected to take place, as some forest categories will find more suitable conditions in previously unsuitable locations, while for other categories the same new conditions will become less suited. A decrease in species diversity is projected in most of the area, with Alpine region showing the potentiality to become a refuge for species migration. To see the webgis app showing the results please visit the following link ArcGis Online http://arcg.is/1mKLi8
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The most comprehensive dataset of in situ destructive sampling measurements of forest biomass in Eurasia have been compiled from a combination of experiments undertaken by the authors and from scientific publications. Biomass is reported as four components: live trees (stem, bark, branches, foliage, roots); understory (above-and below ground); green forest floor (above-and below ground); and coarse woody debris (snags, logs, dead branches of living trees and dead roots), consisting of 10,351 unique records of sample plots and 9,613 sample trees from ca 1,200 experiments for the period 1930–2014 where there is overlap between these two datasets. The dataset also contains other forest stand parameters such as tree species composition, average age, tree height, growing stock volume, etc., when available. Such a dataset can be used for the development of models of biomass structure, biomass extension factors, change detection in biomass structure, investigations into biodiversity and species distribution and the biodiversity-productivity relationship, as well as the assessment of the carbon pool and its dynamics, among many others.
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Stand-level process-based models have rarely been applied to uneven-aged forests that contain many size classes and negative exponential shaped size distributions. However, the relative simplicity of such models, in terms of parameterisation, use and interpretation, could make them valuable tools for studying and managing such forests. In particular, the effects of climate change on the stand-level growth of forests with negative exponential shaped size distributions has received very little attention compared with even-aged forests. The first objective of this study was to validate 3-PG, a stand-level process-based model, for five types of uneven-aged forests in Switzerland; (1) Fagus sylvatica dominated, (2) Picea abies dominated, (3) mixtures of Picea abies and Abies alba, (4) mixtures of Picea abies, Abies alba and Fagus sylvatica, and (5) mixtures of Larix decidua, Pinus cembra and P. abies. The second objective was to use 3-PG to examine how climate change has influenced the growth of these forests since the 1930s. 3-PG predictions of biomass, biomass partitioning in above- and belowground components, and light absorption were validated using inventory data from 23 plots, which had been monitored for an average of 81 years (15 to 112 years). For all species and size classes (2–3 per species), 3-PG produced accurate predictions of root biomass, stem biomass and outputs derived from it such as mean diameter, basal area and height, which were all highly correlated with the observed values (R² > 0.86). The slope of predicted versus observed values was often not significantly different to 1 (averaged 1.13) and the bias averaged −1.2%. 3-PG simulations to examine the effects of climate change without the confounding effects of stand structure and management, showed that the growth of the five forests types has, on average, increased by 17% since the 1930s. The growth was mainly influenced by temperature, while in the case of A. alba, growth was largely influenced by vapour pressure deficit. The accelerated growth rates imply that thinning intensities also need to increase to prevent high stand densities from inhibiting regeneration in these uneven-aged forests. This study shows that 3-PG can be used to predict the growth dynamics of uneven-aged mixed-species forests, and to our knowledge, this is the first time a stand-level process-based forest growth model has been used and validated for such forests.
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Extreme weather events are increasing in frequency and intensity due to global climate change. We hypothesized that tree carbon reserves are crucial for resilience of beech, buffering the source-sink imbalance due to late frosts and summer droughts, and that different components of non-structural carbohydrates (NSCs) play specific roles in coping with stressful situations. To assess the compound effects on mature trees of two extreme weather events, first a late frost in spring 2016 and then a drought in summer 2017, we monitored the phenology, radial growth and the dynamics of starch and soluble sugars in a Mediterranean beech forest. A growth reduction of 85% was observed after the spring late frost, yet not after the drought event. We observed a strong impact of late frost on starch, which also affected its dynamic at the beginning of the subsequent vegetative season. In 2017, the increase of soluble sugars, associated with starch hydrolysis, played a crucial role in coping with the severe summer drought. NSCs helped to counteract the negative effects of both events, supporting plant survival and buffering source-sink imbalances under stressful conditions. Our findings indicate a strong trade-off between growth and NSC storage in trees. Overall, our results highlight the key role of NSCs on beech trees response to extreme weather events, confirming the resilience of this species to highly stressful events. These insights are useful for assessing how forests may respond to the potential impacts of climate change on ecosystem processes in the Mediterranean area.
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With global warming, the growing season is expected to increase for many regions of the Northern Hemisphere. It is therefore important to represent this mechanism in process-based forest growth models used in climate change impact analysis. 3-PG (Physiological Principles Predicting Growth) is a widely used process-based model that operates on stand-scale and monthly time steps. Yet, this model is currently not able to account for changes in the growing season of deciduous tree species. Therefore, we developed a method to model a dynamic growing season length with 3-PG. This method presents a novel approach to model dynamic leaf phenology with a monthly-time step model. We used a linear regression for calculating leaf onset and leaf senescence dates in response to temperature averages. The changes in the order of magnitude of days are then translated into monthly fractions. Further, we made some improvements to previous approaches of modelling the deciduous leaf cycle with 3-PG and we parameterized two model versions of 3-PG for sessile oak (Quercus petraea (Matt.) Liebl.) stands in Southwest Germany. The two model versions differed in presenting a i) constant and ii) dynamic growing season length. We used these model versions to estimate changes in sessile oak forest productivity under future climate scenarios. By comparing both model versions, we could disentangle the net effect of lengthening of the growing season on stem growth. By the end of the century, we observed on average 3-8 % increase in accumulated stem growth resulting from a lengthening of the growing season. At 1°C temperature increase, the lengthening of the growing season accounted for +3.3 % of accumulated stem growth (assuming unchanged precipitation). Leaf-unfolding advanced on average by 9-15 days and leaf senescence was delayed by 6-11 days for the period 2070-2100 compared to 1985-2015; for simulations of rcp 4.5 and 8.5 respectively. Overall, sessile oak productivity remained rather unchanged under future climate scenarios for Southwest Germany. Yet, we observed significant differences between sites (-6 % to +14 % in mean annual volume increment) as well as for different climate change scenarios and models (-2 % to +11 % in mean annual volume increment). We also modelled and discussed how assumptions on CO 2 fertilization effects influenced 3-PG simulations.
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The effects of short‐term extreme events on tree functioning and physiology are still rather elusive. European beech is one of the most sensitive species to late frost and water shortage. We investigated the intra‐annual C dynamics in stems under such conditions. Wood formation and stem CO2 efflux were monitored in a Mediterranean beech forest for three years (2015–2017), including a late frost (2016) and a summer drought (2017). The late frost reduced radial growth and, consequently, the amount of carbon fixed in the stem biomass by 80%. Stem carbon dioxide efflux in 2016 was reduced by 25%, which can be attributed to the reduction of effluxes due to growth respiration. Counter to our expectations, we found no effects of the 2017 summer drought on radial growth and stem carbon efflux. The studied extreme weather events had various effects on tree growth. Even though late spring frost had a strong impact on beech radial growth in the current year, trees fully recovered in the following growing season, indicating high resilience of beech to this stressful event. This article is protected by copyright. All rights reserved.
Article
The effects of short-term extreme events on tree functioning and physiology are still rather elusive. European beech is one of the most sensitive species to late frost and water shortage. We investigated the intra-annual C dynamics in stems under such conditions. Wood formation and stem CO2 efflux were monitored in a Mediterranean beech forest for 3 years (2015-2017), including a late frost (2016) and a summer drought (2017). The late frost reduced radial growth and, consequently, the amount of carbon fixed in the stem biomass by 80%. Stem carbon dioxide efflux in 2016 was reduced by 25%, which can be attributed to the reduction of effluxes due to growth respiration. Counter to our expectations, we found no effects of the 2017 summer drought on radial growth and stem carbon efflux. The studied extreme weather events had various effects on tree growth. Even though late spring frost had a strong impact on beech radial growth in the current year, trees fully recovered in the following growing season, indicating high resilience of beech to this stressful event.
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Key message The change in forest productivity was simulated in six stands in Wallonia (Belgium) following different climate scenarios using a process-based and spatially explicit tree growth model. Simulations revealed a strong and positive impact of the CO 2 fertilization while the negative effect of the transpiration deficit was compensated by longer vegetation periods. The site modulated significantly the forest productivity, mainly through the stand and soil characteristics. ContextForest net primary production (NPP) reflects forest vitality and is likely to be affected by climate change.AimsSimulating the impact of changing environmental conditions on NPP and two of its main drivers (transpiration deficit and vegetation period) in six Belgian stands and decomposing the site effect.Methods Based on the tree growth model HETEROFOR, simulations were performed for each stand between 2011 and 2100 using three climate scenarios and two CO2 modalities (constant vs time dependent). Then, the climate conditions, soils and stands were interchanged to decompose the site effect in these three components.ResultsIn a changing climate with constant atmospheric CO2, NPP values remained constant due to a compensation of the negative effect of increased transpiration deficit by a positive impact of longer vegetation periods. With time-dependent atmospheric CO2, NPP substantially increased, especially for the scenarios with higher greenhouse gas (GHG) emissions. For both atmospheric CO2 modalities, the site characteristics modulated the temporal trends and accounted in total for 56 to 73% of the variability.Conclusion Long-term changes in NPP were primarily driven by CO2 fertilization, reinforced transpiration deficit, longer vegetation periods and the site characteristics.
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Changing environmental conditions may substantially interact with site quality and forest stand characteristics, and impact forest growth and carbon sequestration. Understanding the impact of the various drivers of forest growth is therefore critical to predict how forest ecosystems can respond to climate change. We conducted a continental-scale analysis of recent (1995–2010) forest volume increment data (ΔVol, m³ ha⁻¹ yr⁻¹), obtained from ca. 100,000 coniferous and broadleaved trees in 442 even-aged, single-species stands across 23 European countries. We used multivariate statistical approaches, such as mixed effects models and structural equation modelling to investigate how European forest growth respond to changes in 11 predictors, including stand characteristics, climate conditions, air and site quality, as well as their interactions. We found that, despite the large environmental gradients encompassed by the forests examined, stand density and age were key drivers of forest growth. We further detected a positive, in some cases non-linear effect of N deposition, most pronounced for beech forests, with a tipping point at ca. 30 kg N ha⁻¹ yr⁻¹. With the exception of a consistent temperature signal on Norway spruce, climate-related predictors and ground-level ozone showed much less generalized relationships with ΔVol. Our results show that, together with the driving forces exerted by stand density and age, N deposition is at least as important as climate to modulate forest growth at continental scale in Europe, with a potential negative effect at sites with high N deposition.
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Vegetation nutrient limitation is essential for understanding ecosystem responses to global change. In particular, leaf nitrogen (N) is known to be plastic under changed nutrient limitation. However, models can often not capture these observed changes, leading to erroneous predictions of whole‐ecosystem stocks and fluxes. We hypothesise that an optimality approach can improve representation of leaf N content compared to existing empirical approaches. Unlike previous optimality‐based approaches, which adjust foliar N concentrations based on canopy carbon export, we use a maximisation criteria based on whole‐plant growth and allow for a lagged response of foliar N to this maximisation criterion to account for the limited plasticity of this plant trait. We test these model variants at a range of Free‐Air CO2 Enrichment (FACE) and N fertilisation experimental sites. We show a model solely based on canopy carbon export fails to reproduce observed patterns and predicts decreasing leaf N content with increased N availability. However, an optimal model which maximises total plant growth can correctly reproduce the observed patterns. The optimality model we present here is a whole‐plant approach which reproduces biologically realistic changes in leaf N and can thereby improve ecosystem‐level predictions under transient conditions.
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Two simplifying hypotheses have been proposed for whole‐plant respiration. One links respiration to photosynthesis; the other to biomass. Using a first‐principles carbon balance model with a prescribed live woody biomass turnover, applied at a forest research site where multidecadal measurements are available for comparison, we show that if turnover is fast the accumulation of respiring biomass is low and respiration depends primarily on photosynthesis; while if turnover is slow the accumulation of respiring biomass is high and respiration depends primarily on biomass. But the first scenario is inconsistent with evidence for substantial carryover of fixed carbon between years, while the second implies far too great an increase in respiration during stand development – leading to depleted carbohydrate reserves and an unrealistically high mortality risk. These two mutually incompatible hypotheses are thus both incorrect. Respiration is not linearly related either to photosynthesis or to biomass, but it is more strongly controlled by recent photosynthates (and reserve availability) than by total biomass.
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Frost events during the active growth period of plants can cause extensive frost damage with tremendous economic losses and dramatic ecological consequences. A common assumption is that climate warming may bring along a reduction in the frequency and severity of frost damage to vegetation. On the other hand, it has been argued that rising temperature in late winter and early spring might trigger the so called “false spring”, i.e., early onset of growth that is followed by cold spells, resulting in increased frost damage. By combining daily gridded climate data and 1489k in situ phenological observations of 27 tree species from 5565 phenological observation sites in Europe, we show here that temporal changes in the risk of spring frost damage with recent warming vary largely depending on the species and geographical locations. Species whose phenology was especially sensitive to climate warming tended to have increased risk of frost damage. Geographically, compared with continental areas, maritime and coastal areas in Europe were more exposed to increasing occurrence of frost and these late spring frosts were getting more severe in the maritime and coastal areas. Our results suggest that even though temperatures will be elevated in the future, some phenologically responsive species and many populations of a given species will paradoxically experience more frost damage in the future warming climate. More attention should be paid to the increased frost damage in responsive species and populations in maritime areas when developing strategies to mitigate the potential negative impacts of climate change on ecosystems in the near future. This article is protected by copyright. All rights reserved.
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Purpose: Droughts are expected to become more intense and frequent. Mixed forests can be more resilient to extreme events, but are the individual trees in mixed forests also more resilient to drought? Methods: We sampled 275 trees in 53 temperate forest stands in northern Belgium: monocultures, two-species mixtures, and the three-species mixture of Fagus sylvatica, Quercus robur, and Q. rubra. We related the annual basal area increment of individual trees to drought severity from 1955 to 2015 and calculated growth resistance, recovery, and resilience for six contrasting drought episodes (spring, summer, or full-year drought). Results: Tree growth of the diffuse-porous F. sylvatica was more sensitive to drought, summer drought in particular. The ring-porous Q. robur and Q. rubra were mainly affected by spring drought. In general, a tree's growth response to drought was not affected by tree species diversity, but some identity effects emerged. Conclusion: The asynchrony in drought responses among the tree species (a large and immediate decrease in growth followed by swift recovery in F. sylvatica vs a smaller delayed response in Quercus) might stabilize productivity in forests in which both are present. The impact of the predicted increasing drought frequency will depend on the timing of the droughts (spring vs summer).
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The CORDEX.be project created the foundations for Belgian climate services by producing high-resolution Belgian climate information that (a) incorporates the expertise of the different Belgian climate modeling groups and that (b) is consistent with the outcomes of the international CORDEX (“COordinated Regional Climate Downscaling Experiment”) project. The key practical tasks for the project were the coordination of activities among different Belgian climate groups, fostering the links to specific international initiatives and the creation of a stakeholder dialogue. Scientifically, the CORDEX.be project contributed to the EURO-CORDEX project, created a small ensemble of High-Resolution (H-Res) future projections over Belgium at convection-permitting resolutions and coupled these to seven Local Impact Models. Several impact studies have been carried out. The project also addressed some aspects of climate change uncertainties. The interactions and feedback from the stakeholder dialogue led to different practical applications at the Belgian national level.
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Although numerous species distribution models have been developed, most were based on insufficient distribution data or used older climate change scenarios. We aimed to quantify changes in projected ranges and threat level by the years 2061-2080, for 12 European forest tree species under three climate change scenarios. We combined tree distribution data from the Global Biodiversity Information Facility, EUFORGEN and forest inventories, and we developed species distribution models using MaxEnt and 19 bioclimatic variables. Models were developed for three climate change scenarios – optimistic (RCP2.6), moderate (RCP4.5) and pessimistic (RPC8.5) – using three General Circulation Models, for the period 2061-2080. Our study revealed different responses of tree species to projected climate change. The species may be divided into three groups: “winners” – mostly late-successional species: Abies alba, Fagus sylvatica, Fraxinus excelsior, Quercus robur and Q. petraea; “losers” – mostly pioneer species: Betula pendula, Larix decidua, Picea abies and Pinus sylvestris and alien species – Pseudotsuga menziesii, Q. rubra and Robinia pseudoacacia, which may be also considered as “winners”. Assuming limited migration, most of the species studied would face significant decrease of suitable habitat area. The threat level was highest for species that currently have the northernmost distribution centers. Ecological consequences of the projected range contractions would be serious for both forest management and nature conservation. This article is protected by copyright. All rights reserved.