The loss of pristine old-growth boreal forest landscapes due to the intensive management for timber production has caused both a severe decline of forest biodiversity in Northern Europe as well as significantly altered their carbon stocks and dynamics. Understanding of the dynamics of old-growth forests is needed to evaluate the consequences of different forest management and conservation strategies on climate change mitigation and biodiversity conservation. It is increasingly suggested that integrated forest management and conservation planning is required to secure both biodiversity and carbon storage values. However, it is insufficiently known how closely these values coincide at the local level, i.e., whether the same structural and quality features in old-growth forests support both high biodiversity and carbon stock.The objectives of this study were, first, to explore the dynamics of stand growth and carbon sequestration in boreal old-growth forests and second, to investigate whether the occurrence of red-listed epiphytic forest lichens coincides with high carbon stock and structural features related to it. The study was based on an extensive repeated forest inventory dataset collected between 1990 and 2019 in southern Finland and a lichen inventory conducted during 2020 – 2021 at the same sites.The estimated volume of standing trees and deadwood were higher in the studied forest stands than in managed forests on average. Estimates of net primary production showed varying trends of carbon sequestration among the study plots. Stand gross growth increased by 50% during the study period. The standing volume remained stable because a large proportion of the biomass increment was allocated to deadwood. The study sites showed a high occurrence of red-listed epiphytic lichens. No relationship was found between the species richness of red-listed lichens and the aboveground carbon stock. However, a significant negative relationship was found between the number of red-listed lichen occurrences and carbon stock. The species richness of red-listed lichens showed a strong unimodal response to the aboveground carbon stock change: the highest species richness was associated with intermediate carbon sinks.Our results highlight the major role of tree mortality driving the carbon dynamics of old-growth forests, with simultaneous benefits for deadwood-associated species. However, more research is needed on the stability of carbon stocks of forests in the face of shifting disturbance regimes due to climate change. While the species richness of red-listed epiphytic lichens had a neutral relationship with the aboveground carbon stock size, we observed fewer occurrences in carbon-rich forests, and lower species richness and occurrences in plots with large carbon sinks. Therefore, if climate benefits are sought with methods that increase stand density, negative impacts may be expected on lichen species that fare poorly in dense stands with low light. Additionally, high carbon sequestration in fast-growing stands may come at the expense of reduced biodiversity.In summary, this study supports the idea that old-growth forests provide considerable benefits regarding both climate change mitigation and biodiversity. Therefore, increasing the area of old-growth forests would simultaneously support these key goals.

A scientific evaluation of site quality is essential for the sustainable management of forest ecosystems. However, the absence of a standardized evaluation framework has resulted in site quality assessments that are not comparable across different broadleaf forest types on large spatial scales, impacting forest management decisions related to afforestation, thinning, and carbon sink management. Therefore, establishing a methodological framework for evaluating the site quality of various broadleaf stands could provide practical implications for forestry. Using the data from four cycles of the National Forest Inventory (NFIs) of China, the Richards, Logistic, and Korf models were applied to simulating the growth of 18 major groups of broadleaf trees. We fitted guide curves using the models and constructed site productivity index models for each group. A generalized site productivity index model for broadleaf stands was developed using conversion coefficients between species, with subsequent applicability testing and spatial analysis to assess dynamic changes in site productivity. Results indicate that the Richards model, with an average coefficient of determination (R2) of 0.91, performed better than the Logistic and Korf models. Statistical tests show that the site productivity index models of major broadleaf stands achieve accuracy rates exceeding 90%. The Spearman correlation coefficient is greater than 0.99 between the productivity index classes based on generalized and specific models, demonstrating both the reliability and applicability of the generalized model. Proportional and spatial analyses indicate a continuous trend of improvement in the site productivity of broadleaf stands from 2003 to 2018. The generalized productivity index model based on the relationship between age and biomass was validated by feasibility tests, making it suitable for application in forestry management and prediction. A continuous improvement trend in the site productivity of broadleaf forest was demonstrated, despite fluctuations during short intervals related to uncertainties in our models, which provided a robust, large-scale tool for evaluating forest productivity, offering critical support for sustainable forest management, policy-making, and carbon sequestration strategies in China.

Spatially explicit information of forest status is important for obtaining more accurate predictions of C balance. Spatially explicit predictions of forest characteristics at high resolution can be obtained by Earth Observations (EO), but the accuracy of satellite-based predictions may vary significantly. Modern computational techniques, such as data assimilation (DA), allow us to improve the accuracy of predictions considering measurement uncertainties. The main objective of this work was to develop two DA frameworks that combine repeated satellite measurements (Sentinel-2) and process-based forest model predictions. For the study three tiles of 100 x 100 km2 were considered, in boreal forests. One framework was used to predict forest structural variables and tree species, while the other was used to quantify the site fertility class. The reliability of the frameworks was tested using field measurements. By means of DA we combined model and satellite-based predictions improving the reliability and robustness of forest monitoring. The DA frameworks reduced the uncertainty associated with forest structural variables and mitigated the effects of biased Earth Observation predictions when errors occurred. For one tile, Sentinel-2 prediction for 2019 (s2019) of stem diameter (D) and height (H) was biased, but the errors were reduced by the DA estimation (DA2019). The root mean squared errors were reduced from 5.8 cm (s2019) to 4.5 cm (DA2019) and from 5.1 m (s2019) to 3.3 m (DA2019) for D (sd = 4.33 cm) and H (sd = 3.43 m), respectively. For the site fertility class estimation DA was less effective, because forest growth rate is low in boreal environments; long term analysis might be more informative. We showed here the potential of the DA framework implemented using medium resolution remote sensing data and a process-based forest model. Further testing of the frameworks using more RS-data acquisitions is desirable and the DA process would benefit if the error of satellite-based predictions were reduced.

Regional and national level projections of forest growth, productivity and carbon sequestration are in high demand for policy makers to understand the impacts of climate change and forest management on ecosystem services. The rapid environmental change has accentuated the need of environmentally sensitive forest models that are simultaneously capable of simulating the development of forests under different management regimes and from an initial state defined in terms of standard forest mensuration variables. Efforts to make environmentally sensitive process models more management oriented have been supported by recent developments in model-data assimilation, allowing for quantitatively reliable, policy-relevant projections. However, while the processes related to forest C balance are quite well understood, possible future changes of nitrogen availability still remain a challenge for modelling, as empirical results are few and theories have not converged to a consensus. This is particularly important for the boreal zone where forests are generally regarded as N limited. PREBAS is a management-sensitive carbon-balance model that has been calibrated to forest mensuration type data in Finland. In the calibration, N availability was assumed to be derivable from empirical site quality classification. Following empirical observations and predictions from theoretical models, site quality influences fine-root foliage ratio and stand carrying capacity in PREBAS. The model has been linked with a soil C balance model, Yasso. The combined model incorporates environmental impacts on photosynthesis, respiration, litter fall and soil organic matter decomposition. The model system has been found to produce a spatial distribution of national forest growth and C balance levels in Finland that are well comparable with forest statistics and the Finnish national greenhouse gas inventory, and it has also been evaluated more widely in Northern Europe. The objective of this study was to examine the implications of different future N availabilities on PREBAS projections under climate change. For this, we carried out simulations in a set of 35 sites across a climatic transect and with variable site quality. For these sites we first estimated stand nitrogen requirement on the basis of growth, litter fall and tissue N concentration under maximum canopy cover and in current climate. We then postulated that N uptake depends on N availability and fine root biomass, and estimated N availability by demanding that N uptake should match the N requirement. Based on the results, we developed a method for estimating carrying capacity and below-ground allocation on the basis of changes in the relative availabilities of carbon and nitrogen. We tested the method by simulating growth in a hypothetical FACE experiment, which showed results qualitatively consistent with the literature of ectomycorrhiza-dominated forests. We then compared three different assumptions of changing nitrogen availability under climate change: 1) no change, 2) change is derivable from changing SOM decomposition rate, and 3) N availability increases in pace with N requirement. These were applied in country-wide simulations under different climate scenarios. The plausibility of the scenarios and results are discussed in the light of previous literature.

Browning of surface waters due to increased terrestrial loading of dissolved organic matter (DOM) is observed across the Northern Hemisphere. The effects influence several ecosystem services from freshwater productivity to water purification. Brownification is often explained by changes in large-scale anthropogenic pressures and ecosystem functioning (acidification, climate change, and land cover changes). This study examined the effect of forest use changes on water browning in Finland, considering the effects of global pressures. Our goal was to find the ecosystems and geographic areas that are most sensitive to environmental pressures that increase the loading of DOM. We were also looking for land use strategies that decrease browning. We combined mathematical watershed modelling to scenarios of climate change, atmospheric deposition, and forest use change. Changes included scenarios of forest harvest and protection on forest, that were derived from European Union’s regulation. The study area covered 20 watersheds from south to north of Finland. In northern Finland brownification continue. In southern Finland global influence (atmospheric deposition, climate change) seem to weaken, giving more space for local forest use change having an influence on brownification. Forest use change was more influential in river basins dominated by organic soils than in mineral soils. Extending forest protection decreased brownification especially in areas where the influence of atmospheric pressure is decreasing. When forest protection is planned to provide a carbon storage and sequestration potential and to favor biodiversity, it has favorable effect on surface water quality as well.

Traditional photosynthesis-driven growth models have considerable uncertainties in predicting tree growth under changing climates, partially because sink activities are directly affected by the environment but not adequately addressed in growth modelling. Therefore, we developed a semi-mechanistic model coupling stomatal optimality, temperature control of enzymatic activities and phenology of cambial growth. Parameterized using Bayesian inference and measured data on Picea abies and Pinus sylvestris in peatland and mineral soils in Finland, the coupled model simulates transpiration and assimilation rates and stem radial dimension (SRD) simultaneously at 30 min resolution. The results suggest that both the sink and phenological formulations with environmental effects are indispensable for capturing SRD dynamics across hourly to seasonal scales. Simulated using the model, growth was more sensitive than assimilation to temperature and soil water, suggesting carbon gain is not driving growth at the current temporal scale. Also, leaf-specific production was occasionally positively correlated with growth duration but not with growth onset timing or annual cambial area increment. Thus, as it is hardly explained by carbon gain, phenology itself should be included in sink-driven growth models of the trees in the boreal zone and possibly other environments where sink activities and photosynthesis are both restrained by harsh conditions.

Forests provide important ecosystem services (ESs), including climate change mitigation, local climate regulation, habitat for biodiversity, wood and non-wood products, energy, and recreation. Simultaneously, forests are increasingly affected by climate change and need to be adapted to future environmental conditions. Current legislation, including the European Union (EU) Biodiversity Strategy, EU Forest Strategy, and national laws, aims to protect forest landscapes, enhance ESs, adapt forests to climate change, and leverage forest products for climate change mitigation and the bioeconomy. However, reconciling all these competing demands poses a tremendous task for policymakers, forest managers, conservation agencies, and other stakeholders, especially given the uncertainty associated with future climate impacts. Here, we used process-based ecosystem modeling and robust multi-criteria optimization to develop forest management portfolios that provide multiple ESs across a wide range of climate scenarios. We included constraints to strictly protect 10% of Europe's land area and to provide stable harvest levels under every climate scenario. The optimization showed only limited options to improve ES provision within these constraints. Consequently, management portfolios suffered from low diversity, which contradicts the goal of multi-functionality and exposes regions to significant risk due to a lack of risk diversification. Additionally, certain regions, especially those in the north, would need to prioritize timber provision to compensate for reduced harvests elsewhere. This conflicts with EU LULUCF targets for increased forest carbon sinks in all member states and prevents an equal distribution of strictly protected areas, introducing a bias as to which forest ecosystems are more protected than others. Thus, coordinated strategies at the European level are imperative to address these challenges effectively. We suggest that the implementation of the EU Biodiversity Strategy, EU Forest Strategy, and targets for forest carbon sinks require complementary measures to alleviate the conflicting demands on forests.

Forest management methods and harvest intensities influence wood production, carbon sequestration and biodiversity. We devised different management scenarios by means of stakeholder analysis and incorporated them in the forest growth simulator PREBAS. To analyse impacts of harvest intensity, we used constraints on total harvest: business as usual, low harvest, intensive harvest and no harvest. We carried out simulations on a wall-to-wall grid in Finland until 2050. Our objectives were to (1) test how the management scenarios differed in their projections, (2) analyse the potential wood production, carbon sequestration and biodiversity under the different harvest levels, and (3) compare different options of allocating the scenarios and protected areas. Harvest level was key to carbon stocks and fluxes regardless of management actions and moderate changes in proportion of strictly protected forest. In contrast, biodiversity was more dependent on other management variables than harvesting levels, and relatively independent of carbon stocks and fluxes.

The study of atmospheric processes related to climate requires a multidisciplinary approach, encompassing physics, chemistry, meteorology, forest science, and environmen-tal science. The Academy of Finland Centre of Excellence in atmospheric sciences (CoE ATM) responded to that need for 18 years and produced extensive research and eloquent results, which are summarized in this review. The work in the CoE ATM enhanced our understanding in biogeochemical cycles, ecosystem processes, dynamics of aerosols, ions and neutral clusters in the lower atmosphere, and cloud formation and their interactions and feedbacks. The CoE ATM combined continuous and comprehensive long-term in-situ observations in various environments, ecosystems and platforms, ground-and satellite -based remote sensing, targeted laboratory and field experiments, and advanced multi-scale modeling. This has enabled improved conceptual understanding and quantifications across relevant spatial and temporal scales. Overall, the CoE ATM served as a platform for the multidisciplinary research community to explore the interactions between the biosphere and atmosphere under a common and adaptive framework.

The EU aims at reaching carbon neutrality by 2050 and Finland by 2035. We integrated results of three spatially distributed model systems (FRES, PREBAS, Zonation) to evaluate the potential to reach this goal at both national and regional scale in Finland, by simultaneously considering protection targets of the EU biodiversity (BD) strategy. Modelling of both anthropogenic emissions and forestry measures were carried out, and forested areas important for BD protection were identified based on spatial prioritization. We used scenarios until 2050 based on mitigation measures of the national climate and energy strategy, forestry policies and predicted climate change, and evaluated how implementation of these scenarios would affect greenhouse gas fluxes, carbon storages, and the possibility to reach the carbon neutrality target. Potential new forested areas for BD protection according to the EU 10% protection target provided a significant carbon storage (426-452 TgC) and sequestration potential (- 12 to - 17.5 TgCO(2)eq a(-1)) by 2050, indicating complementarity of emission mitigation and conservation measures. The results of the study can be utilized for integrating climate and BD policies, accounting of ecosystem services for climate regulation, and delimitation of areas for conservation.

Forest net biome exchange and carbon stock projections with uncertainty by regions of the mainland Finland over period 2015-2050. Projections under three climate scenarios, RCP2.6, RCP4.5, and RCP8.5, and four harvest scenarios - BaseHarv (historical average harvest level of the years 2015-2021), slightly more intensive harvests MaxHarv (1.2 x BaseHarv), lower harvest intensity LowHarv (0.6 x BaseHarv) and no harvests after the year 2021 NoHarv - for each administrative region (NUTS3), and as aggregated from all the regions to the whole country, are given. The files contain mean value and 2.5%, 5%, 25%, 75%, 95% and 97.5% quantiles of the average Net Biome emissions (file NBEave.xlsx) and total carbon stock (file Cstockave.xlsx). The forest areas (forest land and poorly productive forest land, excluding undrained peatlands), and areas of mineral soils and drained organic soils for each region and the whole mainland of Finland are given in file areas.xlsx. Description of the used data and methods are given in article:Junttila, V., Minunno, F., Peltoniemi, M. et al. Quantification of forest carbon flux and stock uncertainties under climate change and their use in regionally explicit decision making: Case study in Finland. Ambio (2023). https://doi.org/10.1007/s13280-023-01906-4

We present regionally aggregated emissions of greenhouse gases (GHG) from five land cover categories in Finland: artificial surfaces, arable land, forest, waterbodies, and wetlands. Carbon (C) sequestration to managed forests and unmanaged wetlands was also assessed. Models FRES and ALas were applied for emissions (CO2, CH4, N2O) from artificial surfaces and agriculture, and PREBAS for forest growth and C balance. Empirical emission coefficients were used to estimate emissions from drained forested peatland (CH4, N2O), cropland (CO2), waterbodies (CH4, CO2), peat production sites and undrained mires (CH4, CO2, N2O). We calculated gross emissions of 147.2 ± 6.8 TgCO2eq yr−1 for 18 administrative units covering mainland Finland, using data representative of the period 2017–2025. Emissions from energy production, industrial processes, road traffic and other sources in artificial surfaces amounted to 45.7 ± 2.0 TgCO2eq yr−1. The loss of C in forest harvesting was the largest emission source in the LULUCF sector, in total 59.8 ± 3.3 TgCO2eq yr−1. Emissions from domestic livestock production, field cultivation and organic soils added up to 12.2 ± 3.5 TgCO2eq yr−1 from arable land. Rivers and lakes (13.4 ± 1.9 TgCO2eq yr−1) as well as undrained mires and peat production sites (14.7 ± 1.8 TgCO2eq yr−1) increased the total GHG fluxes. The C sequestration from the atmosphere was 93.2 ± 13.7 TgCO2eq yr−1. with the main sink in forest on mineral soil (79.9 ± 12.2 TgCO2eq yr−1). All sinks compensated 63

Uncertainties are essential, yet often neglected, information for evaluating the reliability in forest carbon balance projections used in national and regional policy planning. We analysed uncertainties in the forest net biome exchange (NBE) and carbon stocks under multiple management and climate scenarios with a process-based ecosystem model. Sampled forest initial state values, model parameters, harvest levels and global climate models (GCMs) served as inputs in Monte Carlo simulations, which covered forests of the 18 regions of mainland Finland over the period 2015-2050. Under individual scenarios, the results revealed time- and region-dependent variability in the magnitude of uncertainty and mean values of the NBE projections. The main sources of uncertainty varied with time, by region and by the amount of harvested wood. Combinations of uncertainties in the representative concentration pathways scenarios, GCMs, forest initial values and model parameters were the main sources of uncertainty at the beginning, while the harvest scenarios dominated by the end of the simulation period, combined with GCMs and climate scenarios especially in the north. Our regionally explicit uncertainty analysis was found a useful approach to reveal the variability in the regional potentials to reach a policy related, future target level of NBE, which is important information when planning realistic and regionally fair national policy actions.

The challenges of applying process-based models to uneven-aged forests are the difficulties in simulating the interactions between trees and resource allocation between size classes. In this study, we focused on a process-based forest growth model PREBAS which is a mean tree model with Reineke self-thinning mortality and was originally developed for even-aged forests. The primary aim was to test the application of PREBAS model to uneven-aged forests by introducing different diameter at breast height (DBH) size classes to better represent the forest structure. Additionally, we introduced a new mortality model MORnew to PREBAS which is developed for uneven-aged stands and compared with the current PREBAS version in which a modification Reineke rule is used. The tests were conducted in 26 old Norway spruce dominated stands in southern and central Finland with three consecutive measurements (on average a 25-year study period). To evaluate the model performance, we compared the estimations of stand averaged diameter at breast height (D), stand averaged tree height (H), stand averaged crown base height (Hc), stand basal area (B) and density (N) with measurements. Moreover, biomass estimations of each tree component (foliage, branch and stem) were compared to estimations from empirical models. Results showed that introducing size distributions can represent better stand structure and improve the model predictions compared with data. Moreover, the new mortality model MORnew showed promise with qualitatively more realistic results especially among the largest tree size classes. However, model bias still existed in the simulation although the predictions were improved. It revealed that further calibration of the PREBAS model with size classes should be done to better extend the model applicability to uneven-aged forests.

Forest conservation plays a central role in meeting national and international biodiversity and climate targets. Biodiversity and carbon values within forests are often estimated with models, introducing uncertainty to decision making on which forest stands to protect. Here, we explore how uncertainties in forest variable estimates affect modelled biodiversity and carbon patterns, and how this in turn introduces variability in the selection of new protected areas. We find that both biodiversity and carbon patterns were sensitive to alterations in forest attributes. Uncertainty in features that were rare and/or had dissimilar distributions with other features introduced most variation to conservation plans. The most critical data uncertainty also depended on what fraction of the landscape was being protected. Forests of highest conservation value were more robust to data uncertainties than forests of lesser conservation value. Identifying critical sources of model uncertainty helps to effectively reduce errors in conservation decisions.

Continuous cover forestry has been proposed as a method for simultaneously maintaining diversity, wood production and carbon storage of forests. Uneven-aged (UEA) management of Norway spruce ( Picea abies (L.) Karst.) is the most common method of continuous cover forestry in Fennoscandia. Despite of increasing research intensity, we are still lacking established quantitative tools to compare the different silvicultural systems. In this study we used a process-based stand growth model, PipeQual, which has previously been evaluated against data from stands under even-aged management (EA). We first adapted the model to uneven-aged stands and evaluated it against 16 years of growth of 14 Norway spruce stands from a long-term UEA experiment (ERIKA) in southern Finland. We then applied the model to compare growth, yield and carbon sequestration under EA and UEA management. For the EA stands we used 11 different plausible harvest schedules for two site fertilities, compared with the 14 UEA sites under two different selection rules. EA results were averaged over one rotation and UEA results were averaged over 120 years. The model evaluation produced satisfactory results of mean-tree growth, mortality and ingrowth in diameter classes, with a slight exaggeration of diameter growth in mid-size trees. The performance improved with the level of aggregation from size-class means to size-class totals and further to stand totals. In the management comparison, no significant difference was found in the mean annual increment (MAI) between the management methods, but the yield of UEA was 15% less than that of EA due to mortality. The carbon storage of tree stock was larger under EA than UEA because of the relatively low density recommended in UEA stands. Litter fall, i.e., carbon input to the soil, was marginally larger in the UEA stands, largely due to tree mortality. These results were obtained assuming that the level of ingrowth of 1.3 m seedlings in all stands corresponded to the measured stand average, however, the observed rates of ingrowth varied from zero to 2000 seedlings during the 16-year period. A sensitivity analysis showed that all the simulated flux and stock variables declined rapidly with ingrowth rates lower than the observed average, saturating when ingrowth was approximately doubled. This corroborates previous results according to which productivity under UEA management is strongly dependent on the ingrowth rate which, however, is poorly understood in quantitative terms.

The boreal forest is an important global carbon (C) sink. Since low soil nitrogen (N) availability is commonly a key constraint on forest productivity, the prevalent view is that increased N input enhances its C sink-strength. This understanding however relies primarily on observations of increased aboveground tree biomass and soil C stock following N fertilization, whereas empirical data evaluating the effects on the whole ecosystem-scale C balance are lacking. Here we use a unique long-term experiment consisting of paired forest stands with eddy covariance measurements to explore the effect of ecosystem-scale N fertilization on the C balance of a managed boreal pine forest. We find that the annual C uptake (i.e. net ecosystem production, NEP) at the fertilized stand was 16 +/- 2% greater relative to the control stand by the end of the first decade of N addition. Subsequently, the ratio of NEP between the fertilized and control stand remained at a stable level during the following five years with an average NEP to N response of 7 & PLUSMN; 1 g C per g N. Our study reveals that this non-linear response of NEP to long-term N fertilization was the result of a cross-seasonal feedback between the N-induced increases in both growing-season C uptake and subsequent winter C emission. We further find that one decade of N addition altered the sensitivity of ecosystem C fluxes to key environmental drivers resulting in divergent responses to weather patterns. Thus, our study highlights the need to account for ecosystem-scale responses to perturbations to improve our understanding of nitrogen-carbon-climate feedbacks in boreal forests.

There is evidence that carbon fluxes and stocks decrease with increasing latitude in boreal forests, suggesting a reduction in carbon use efficiency. While vegetation and soil carbon dynamics have been widely studied, the empirical finding that ectomycorrhizal fungi (ECM) become more abundant towards the north has not been quantitatively linked to carbon use efficiency. We formulated a conceptual model of combined fine-root and ECM carbon use efficiency (CUE) as NPP/GPP (net primary production/gross primary production). For this, we included the mycorrhiza as gains in plant NPP but considered the extramatrical hyphae as well as exudates as losses. We quantified the carbon processes across a latitudinal gradient using published eco-physiological and morphological measurements from boreal coniferous forests. In parallel, we developed two CUE models using large-scale empirical measurements amended with established models. All models predicted similar latitudinal trends in vegetation CUE and net ecosystem production (NEP). CUE in the ECM model declined on average by 0.1 from latitude 60 to 70 with overall mean 0.390 +/- 0.037. NEP declined by 200 g m(-2) yr(-1) with mean 171 +/- 79.4 g m(-2) yr(-)(1). ECM had no significant effect on predicted soil carbon. Our findings suggest that ECM can use a significant proportion of the carbon assimilated by vegetation and hence be an important driver of the decline in CUE at higher latitudes. Our model suggests the quantitative contribution of ECM to soil carbon to be less important but any possible implications through litter quality remain to be assessed. The approach provides a simple proxy of ECM processes for regional C budget models and estimates.

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.

Waterlogging causes hypoxic or anoxic conditions in soils, which lead to decreases in root and stomatal hydraulic conductance. Although these effects have been observed in a variety of plant species, they have not been quantified continuously over a range of water table depths (WTD) or soil water contents (SWC). To provide a quantitative theoretical framework for tackling this issue, we hypothesized similar mathematical descriptions of waterlogging and drought effects on whole-tree hydraulics and constructed a hierarchical model by connecting optimal stomata and soil-to-leaf hydraulic conductance models. In the model, the soil-to-root conductance is non-monotonic with WTD to reflect both the limitations by water under low SWC and by hypoxic effects associated with inhibited oxygen diffusion under high SWC. The model was parameterized using priors from literature and data collected over four growing seasons from Scots pine (Pinus sylvestris L.) trees grown in a drained peatland in Finland. Two reference models (RMs) were compared with the new model, RM1 with no belowground hydraulics and RM2 with no waterlogging effects. The new model was more accurate than the RMs in predicting transpiration rate (fitted slope of measured against modeled transpiration rate = 0.991 vs 0.979 (RM1) and 0.984 (RM2), R-2 = 0.801 vs 0.665 (RM1) and 0.776 (RM2)). Particularly, RM2's overestimation of transpiration rate under shallow water table conditions (fitted slope = 0.908, R-2 = 0.697) was considerably reduced by the new model (fitted slope = 0.956, R-2 = 0.711). The limits and potential improvements of the model are discussed.