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The contribution of selected sources of uncertainty to the total variance of model simulation results of stem biomass increment calculated from annual stem biomass predictions of European beech (Fagus sylvatica L.) was quantified. Sources of uncertainty were defined as the selected variables that influence the total variance of the model results. Simulations were made: (i) for ten regional climate models (RCMs) based on the IPCC scenario A1B and providing an ensemble of climate projections up to 2100; (ii) with two forest model types (FMTYPEs); (iii) for four forest management intensities (MANFORs); and (iv) for three time windows (TIMEWINDs), each spanning 15 years, starting in 2019, in 2049 and in 2079. Both models, the empirical SIBYLA model and the process-based ANAFORE model, were calibrated using experimental tree growth data from four plots in central Slovakia between 1989 and 2003. Three of these plots, representing the four MANFORs, were subject to different prior intensities of thinning while one was left untouched as a control. The FMTYPE explained most of the total variance in the simulation results (39.9%), followed by MANFOR (i.e. thinning intensity; 22.2%) and TIMEWIND (12.0%), while the effect of RCMs on model uncertainty was limited (

• Increasing atmospheric concentrations of phytotoxic ozone (O(3) ) can constrain growth and carbon sink strength of forest trees, potentially exacerbating global radiative forcing. Despite progress in the conceptual understanding of the impact of O(3) on plants, it is still difficult to detect response patterns at the leaf level. • Here, we employed principal component analysis (PCA) to analyse a database containing physiological leaf-level parameters of 60-yr-old Fagus sylvatica (European beech) trees. Data were collected over two climatically contrasting years under ambient and twice-ambient O(3) regimes in a free-air forest environment. • The first principal component (PC1) of the PCA was consistently responsive to O(3) and crown position within the trees over both years. Only a few of the original parameters showed an O(3) effect. PC1 was related to parameters indicative of oxidative stress signalling and changes in carbohydrate metabolism. PC1 correlated with cumulative O(3) uptake over preceding days. • PC1 represents an O(3) -responsive multivariate pattern detectable in the absence of consistently measurable O(3) effects on individual leaf-level parameters. An underlying effect of O(3) on physiological processes is indicated, providing experimental confirmation of theoretical O(3) response patterns suggested previously.

Six photosynthesis-dependent stomatal models were tested and compared against twig cuvette gas exchange data for adult common beech ( Fagus sylvatica L.). The models differed in the use of (1) either leaf surface CO 2 concentration ( C s ) or leaf intercellular CO 2 concentration ( C i ), and of (2) either measured environmental humidity variables or a crudely calculated leaf water potential to simulate the effect of drought stress on stomatal conductance. The models applying C s performed slightly better than the models applying C i . The models based on environmental humidity variables performed distinctly better than the models applying a calculated leaf water potential. Several explanations for the observed performance differences between models applying C s or C i were brought forward and discussed.

Phenological events are sensitive to climate change, and a clear advancement of spring leaf phenology has been well documented. However, the observed phenological trends cannot be directly used to forecast future changes because the underlying mechanisms are still unclear. We conducted a two-year experimental warming experiment using one-meter-high saplings of birch (Betula pendula L), oak (Quercus robur L) and beech (Fagus sylvatica L.). The main objective of this study was to quantify the temperature sensitivity of leaf unfolding to six different warming levels. The results suggested that leaf unfolding dates were significantly advanced with warming for all species in both experimental years. However, different warming treatments elicited different leaf unfolding responses. At low and moderate warming (

Budburst phenology is a key driver of ecosystem structure and functioning, and it is sensitive to global change. Both cold winter temperatures (chilling) and spring warming (forcing) are important for budburst. Future climate warming is expected to have a contrasting effect on chilling and forcing, and subsequently to have a non-linear effect on budburst timing. To clarify the different effects of warming during chilling and forcing phases of budburst phenology in deciduous trees, (i) we conducted a temperature manipulation experiment, with separate winter and spring warming treatments on well irrigated and fertilized saplings of beech, birch and oak, and (ii) we analyzed the observations with five temperature-based budburst models (Thermal Time model, Parallel model, Sequential model, Alternating model, and Unified model). The results show that both winter warming and spring warming significantly advanced budburst date, with the combination of winter plus spring warming accelerating budburst most. As expected, all three species were more sensitive to spring warming than to winter warming. Although the different chilling requirement, the warming sensitivity was not significantly different among the studied species. Model evaluation showed that both one- and two- phase models (without and with chilling, respectively) are able to accurately predict budburst. For beech, the Sequential model reproduced budburst dates best. For oak and birch, both Sequential model and the Thermal Time model yielded good fit with the data but the latter was slightly better in case of high parameter uncertainty. However, for late-flushing species, the Sequential model is likely be the most appropriate to predict budburst data in a future warmer climate.

Phenology models are tools to analyze changes in the timing and duration of the growing season. During the past three decades different budburst models have been developed, but, so far, no consensus model has been found to accurately predict budburst date across different tree species. The aim of this study was to estimate the performance of six different temperature-driven models of leaf budburst (thermal time, thermal period fixed, sequential, parallel, alternating, unified) for four temperate tree species in Belgium (birch, chestnut, oak, beech). The models were parameterized using a Bayesian approach. The performance of these models was compared using Bayesian model comparison (BMC) and root mean square error (RMSE). Model comparison showed that the two models that do not include a calculation of chilling requirement were the best for the studied four tree species. The Sequential model (SM) was the third most plausible model for predicting budburst, having a higher probability to be correct than the other two-phase models combining a chilling phase with a forcing phase. This suggested that in our budburst observation dataset, the chilling requirement was probably always fulfilled, making the date of budburst controlled by forcing temperature. We cannot rule out that in warmer regions or future warmer conditions, chilling may become insufficient and a sequential pattern of chilling and forcing may become most appropriate to simulate budburst date. Parameter analysis showed that the last month prior to budburst had the greatest impact on determining the date of bud opening in the case of birch and chestnut, whereas the last 3 months were the main determinants for oak and beech, the two later flushing species. Validation showed that the models that fitted the parameterization data well had much poorer performance when tested with independent data. This indicates that other factors (e.g. photoperiod) might affect the budburst process and/or model parameterization (determining the sensitivity of budburst to temperature) substantially change between different localities. (C) 2012 Elsevier BM. All rights reserved.

Numerous phenology models developed to predict the budburst date of trees have been merged into one Unified model (Chuine, 2000, J. Theor. Biol. 207, 337347). In this study, we tested a simplified version of the Unified model (Unichill model) on six woody species. Budburst and temperature data were available for five sites across Belgium from 1957 to 1995. We calibrated the Unichill model using a Bayesian calibration procedure, which reduced the uncertainty of the parameter coefficients and quantified the prediction uncertainty. The model performance differed among species. For two species (chestnut and black locust), the model showed good performance when tested against independent data not used for calibration. For the four other species (beech, oak, birch, ash), the model performed poorly. Model performance improved substantially for most species when using site-specific parameter coefficients instead of across-site parameter coefficients. This suggested that budburst is influenced by local environment and/or genetic differences among populations. Chestnut, black locust and birch were found to be temperature-driven species, and we therefore analyzed the sensitivity of budburst date to forcing temperature in those three species. Model results showed that budburst advanced with increasing temperature for 13 days °C−1, which agreed with the observed trends. In synthesis, our results suggest that the Unichill model can be successfully applied to chestnut and black locust (with both across-site and site-specific calibration) and to birch (with site-specific calibration). For other species, temperature is not the only determinant of budburst and additional influencing factors will need to be included in the model.

Ground-level ozone (O3) has gained awareness as an agent of climate change. In this respect, key results are comprehended from a unique 8-year free-air O3-fumigation experiment, conducted on adult beech (Fagus sylvatica) at Kranzberg Forest (Germany). A novel canopy O3 exposure methodology was employed that allowed whole-tree assessment in situ under twice-ambient O3 levels. Elevated O3 significantly weakened the C sink strength of the treesoil system as evidenced by lowered photosynthesis and 44% reduction in whole-stem growth, but increased soil respiration. Associated effects in leaves and roots at the gene, cell and organ level varied from year to year, with drought being a crucial determinant of O3 responsiveness. Regarding adult individuals of a late-successional tree species, empirical proof is provided first time in relation to recent modelling predictions that enhanced ground-level O3 can substantially mitigate the C sequestration of forests in view of climate change. Empirical proof corroborates substantial mitigation of carbon sequestration in the treesoil system of a forest site under enhanced O3 impact for adult beech.

The purpose of this study was to expand an existing semi-mechanistic forest model, ANAFORE (ANAlysing Forest Ecosystems), to allow for the prediction of log quality and the accompanying uncertainty as influenced by climate and management. The forest stand is described as consisting of trees of different cohorts, either of the same or of different species (deciduous or coniferous). In addition to photosynthesis, transpiration, total growth and yield, the model simulates the daily evolution in vessel biomass and radius, parenchyma and branch development. From these data early and latewood biomass, wood tissue composition, knot formation and density are calculated. The new version presented here, includes the description of log quality, including red heart formation of beeches. A Bayesian optimisation routine for the species parameters was added to the stand model. From a given range of input parameters (prior), the model calculates an optimised range for the parameters (posterior) based on given output data, as well as an uncertainty on the predicted values. A case study was performed for Slovenian beech forests to illustrate the main model functioning and more in particular the simulation of the wood quality. The results indicate that the ANAFORE model is a useful tool for analyzing wood quality development and forest ecosystem functioning in response to management, climate and stand characteristics. However, the Bayesian optimization showed that the remaining uncertainty on the input parameters for the chosen stand was very large, due to the large number of input parameters in comparison to the limited stand data.

Ozone affects adult trees significantly, but effects on stem growth are hard to prove and difficult to correlate with the primary sites of ozone damage at the leaf level. To simulate ozone effects in a mechanistic way, at a level relevant to forest stand growth, we developed a simple ozone damage and repair model (CASIROZ model) that can be implemented into mechanistic photosynthesis and growth models. The model needs to be parameterized with cuvette measurements on net photosynthesis and dark respiration. As the CASIROZ ozone sub-model calculates effects of the ozone flux, a reliable representation of stomatal conductance and therefore ozone uptake is necessary to allow implementation of the ozone sub-model. In this case study the ozone sub-model was used in the ANAFORE forest model to simulate gas exchange, growth, and allocation. A preliminary run for adult beech (Fagus sylvatica) under different ozone regimes at the Kranzberg forest site (Germany) was performed. The results indicate that the model is able to represent the measured effects of ozone adequately, and to distinguish between immediate and cumulative ozone effects. The results further help to understand ozone effects by distinguishing defence from damage and repair. Finally, the model can be used to extrapolate from the short-term results of the field study to long-term effects on tree growth. The preliminary simulations for the Kranzberg beech site show that, although ozone effects on yearly growth are variable and therefore insignificant when measured in the field, they could become significant at longer timescales (above 5 years, 5 % reduction in growth). The model offers a possible explanation for the discrepancy between the significant effects on photosynthesis (10 to 30 % reductions simulated), and the minor effects on growth. This appears to be the result of the strong competition and slow growth of the Kranzberg forest, and the importance of stored carbon for the adult beeches (by buffering effects on carbon gain). We finally conclude that inclusion of ozone effects into current forest growth and yield models can be an important improvement into their overall performance, especially when simulating younger and less dense forests.

Currently, the most important source of uncertainty in stomatal ozone flux (FO3) modelling is the stomatal conductance (g(st)) factor. Hence FO3 model accuracy will strongly depend on the g,t model being implemented. In this study the recently developed semi-empirical g(st) model of Dewar was coupled to the widely known biochemical photosynthesis (A(n)) model of Farquhar. The g(st) performance of this model combination was evaluated with a 4-month time series of beech (Fagus sylvatica L.) measurements. The g(st) model was hereto optimized in two steps to a 4-day and a 8-day period. A comparison between the modelled and measured g(st) to O-3 (g(stO3)) revealed a rather good overall performance (R-2 = 0.77). Errors between the model combination and the measurements are thought to be largely caused by a moderate performance of the A(n) model, due to poor parameterization. Two 2-day periods with distinctly differing soil and meteorological conditions were chosen to give a picture of the daily g, performance. Although instant relative differences between modelled and measured g(stO3) are sometimes high, the model combination is able to simulate the rough daily courses of g(stO3) and hence FO3 reasonably well. Further improvement on full parameterization of the g, model and a well-parameterized A, model to be linked to are needed to draw founded conclusions about its performance. Future efforts hereto are certainly justified since the model's mechanistic nature makes it a tool able to model g(st) variation in space and time, O-3 effects on g(st), and effective FO3.