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Knowledge about the stand structure and dynamics of subalpine forests is crucial to preserve their multifunctionality. In the present study, we reconstructed the spatiotemporal dynamics of a subalpinePinus cembraforest in the eastern Italian Alps in response to natural disturbances and forest management. We adopted a concurrent point pattern, dendroecological and growth dominance (GD) analysis. We mapped and measured all trees ofPinus cembraandLarix deciduain a 1 ha plot. We analyzed intra- and interspecific spatial patterns and spatial autocorrelation of tree size and age. We explored establishment dynamics and shifts in competition by analyzing growth suppression/release patterns and GD trends. Results showed a clumped, uneven-aged, multilayered structure where pine was dominant. The synergic action of ecological and human-induced factors is discussed to explain the prevalence of pine over time. Spatial pattern and autocorrelation analyses suggest a different colonization strategy of the two species, in which pine established after small-scale perturbations and experienced a stronger inter- and intra-specific competition. The interruption of tree establishment and shift in GD toward large trees resulting from the lack of forest management are the most important findings of this research. This highlights the importance of an active management to avoid the homogenization of the forest structure that is generally associated with a reduction in biodiversity and protective ability of forests. [ABSTRACT FROM PUBLISHER]

• Harmonised freely-available data is crucial to model forest impacts on climate change. • We summarise available datasets on forest functioning and underlying drivers. • Data for key demographic mechanisms are available at the short-term at EU level. • Lack of high-resolution harmonised EU data for genetic and physiological tree responses to climate change. • Need for Pan-European data integration effort. Climate change is expected to cause major changes in forest ecosystems during the 21st century and beyond. To assess forest impacts from climate change, the existing empirical information must be structured, harmonised and assimilated into a form suitable to develop and test state-of-the-art forest and ecosystem models. The combination of empirical data collected at large spatial and long temporal scales with suitable modelling approaches is key to understand forest dynamics under climate change. To facilitate data and model integration, we identified major climate change impacts observed on European forest functioning and summarised the data available for monitoring and predicting such impacts. Our analysis of c. 120 forest-related databases (including information from remote sensing, vegetation inventories, dendroecology, palaeoecology, eddy-flux sites, common garden experiments and genetic techniques) and 50 databases of environmental drivers highlights a substantial degree of data availability and accessibility. However, some critical variables relevant to predicting European forest responses to climate change are only available at relatively short time frames (up to 10-20 years), including intra-specific trait variability, defoliation patterns, tree mortality and recruitment. Moreover, we identified data gaps or lack of data integration particularly in variables related to local adaptation and phenotypic plasticity, dispersal capabilities and physiological responses. Overall, we conclude that forest data availability across Europe is improving, but further efforts are needed to integrate, harmonise and interpret this data (i.e. making data useable for non-experts). Continuation of existing monitoring and networks schemes together with the establishments of new networks to address data gaps is crucial to rigorously predict climate change impacts on European forests. [ABSTRACT FROM AUTHOR]

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

Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all forest landscape models currently applied in temperate European forests (LandClim, TreeMig, LANDIS-II, iLand). We examined the uncertainty of model projections under several future climate, disturbance, and dispersal scenarios, and quantified uncertainties by variance partitioning. While projections under past climate conditions were in good agreement with observations, uncertainty under future climate conditions was high, with between-model biomass differences of up to 200 t ha−1. Disturbances strongly influenced landscape dynamics and contributed substantially to uncertainty in model projections (~25–40% of observed variance). Overall, model differences were the main source of uncertainty, explaining at least 50% of observed variance. We advocate a more rigorous and systematic model evaluation and calibration, and a broader use of ensemble projections to quantify uncertainties in future landscape dynamics. • The first systematic comparison of forest landscape models is presented. • Variance of model projections under several future scenarios is substantial. • Model differences explain most of the simulated variance. [ABSTRACT FROM AUTHOR]