Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long‐term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground‐based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m³ of disturbed timber volume per year over the 70‐year study period. This value is likely a conservative estimate due to under‐reporting, especially of small‐scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m³/year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long‐term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes.

Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions.

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented). Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance.

Soil organic carbon (SOC) is a mandatory pool in national inventory reports on greenhouse gas (GHG) emissions and removals to the UNFCCC. Hence, its accurate assessment is important. Modelling SOC changes for national GHG reports is encouraged, but the uncertainty related to this pool still presents a significant challenge; thus, verifying modelling results with field observations is essential. We used the process-based model Biome-BGCMuSo and assessed its suitability for use in Croatia’s GHG reporting. We modelled SOC stocks in the top 30 cm of the mineral soil layer (SOC₃₀) for four different land-use (LU) categories (Deciduous/Coniferous Forest, Grassland and Annual Cropland) distributed in three biogeographical regions (Alpine, Continental and Mediterranean) and compared them with results of a national soil survey. A total of 573 plot level simulations were undertaken and results were evaluated at three stratification levels (LU, LU × biogeographical region, and plot). The model reproduced the overall country mean of SOC₃₀ with no overall bias, and showed good performance at the LU level with no significant (p < 0.05) difference for all LUs except Deciduous Forest (11% overestimation). At finer stratifications, the model performance considerably worsened. Further model calibration, improvement and testing, as well as repeated soil survey are needed in order to assess the changes in SOC₃₀ and to evaluate the potential of the Biome-BGCMuSo model for use in GHG reporting.

We analysed 10 years (2008–2017) of continuous eddy covariance (EC) CO₂ flux measurements of net ecosystem exchange (NEE) in a young pedunculate oak forest in Croatia. Measured NEE was gap-filled and partitioned into gross primary productivity (GPP) and ecosystem reparation (R_ECO) using the online tool by Max Planck Institute for Biogeochemistry in Jena, Germany. Annual NEE, GPP, and R_ECO were correlated with main environmental drivers. Net primary productivity was estimated from EC (NPP_EC), as a sum of −NEE and R_h obtained using a constant R_h:R_ECO ratio, and from independent periodic biometric measurements (NPP_BM). For comparing the NPP at the seasonal level, we propose a simple model that aimed at accounting for late-summer and autumn carbon storage in the non-structural carbohydrate pool. Over the study period, Jastrebarsko forest acted as a carbon sink, with an average (±std. dev.) annual NEE of −319 (±94) gC m⁻² year⁻¹, GPP of 1594 (±109) gC m⁻² year⁻¹, and R_ECO of 1275 (±94) gC m⁻² year⁻¹. Annual NEE showed high inter-annual variability and poor correlation with annual average global radiation, air temperature, and total precipitation, but significant (R² = 0.501, p = 0.02) correlation with the change in soil water content between May and September. Comparison of annual NPP_EC and NPP_BM showed a good overall agreement (R² = 0.463, p = 0.03), although in all years NPP_BM was lower than NPP_EC, with averages of 680 (±88) gC m⁻² year⁻¹ and 819 (±89) gC m⁻² year⁻¹, respectively. Lower values of NPP_BM indicate that fine roots and grasses contributions to NPP, which were not measured in the study period, could have an important contribution to the overall ecosystem NPP. At a seasonal level, two NPP estimates showed differences in their dynamic, but the application of the proposed model greatly improved the agreement in the second part of the growing season. Further research is needed on the respiration partitioning and mechanisms of carbon allocation.