A harmonized database of European forest simulations under climate change.

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing. Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.

Contrasting patterns of water use efficiency and annual radial growth among European beech forests along the Italian peninsula.

Tree mortality and forest dieback episodes are increasing due to drought and heat stress. Nevertheless, a comprehensive understanding of mechanisms enabling trees to withstand and survive droughts remains lacking. Our study investigated basal area increment (BAI), and δ13C-derived intrinsic water-use-efficiency (iWUE), to elucidate beech resilience across four healthy stands in Italy with varying climates and soil water availability. Additionally, fist-order autocorrelation (AR1) analysis was performed to detect early warning signals for potential tree dieback risks during extreme drought events. Results reveal a negative link between BAI and vapour pressure deficit (VPD), especially in southern latitudes. After the 2003 drought, BAI decreased at the northern site, with an increase in δ13C and iWUE, indicating conservative water-use. Conversely, the southern sites showed increased BAI and iWUE, likely influenced by rising CO2 and improved water availability. In contrast, the central site sustained higher transpiration rates due to higher soil water holding capacity (SWHC). Despite varied responses, most sites exhibited reduced resilience to future extreme events, indicated by increased AR1. Temperature significantly affected beech iWUE and BAI in northern Italy, while VPD strongly influenced the southern latitudes. The observed increase in BAI and iWUE in southern regions might be attributed to an acclimation response.

Simulating diverse forest management options in a changing climate on a Pinus nigra subsp. laricio plantation in Southern Italy.

Mediterranean pine plantations provide several ecosystem services but are vulnerable to climate change. Forest management might play a strategic role in the adaptation of Mediterranean forests, but the joint effect of climate change and diverse management options have seldom been investigated together. Here, we simulated the development of a Laricio pine (Pinus nigra subsp. laricio) stand in the Bonis watershed (southern Italy) from its establishment in 1958 up to 2095 using a state-of-the-science process-based forest model. The model was run under three climate scenarios corresponding to increasing levels of atmospheric CO2 concentration and warming, and six management options with different goals, including wood production and renaturalization. We analysed the effect of climate change on annual carbon fluxes (i.e., gross and net primary production) and stocks (i.e., basal area, standing and harvested carbon woody stocks) of the autotrophic compartment, as well as the impact of different management options compared to a no management baseline. Results show that higher temperatures (+3 to +5 °C) and lower precipitation (-20 % to -22 %) will trigger a decrease in net primary productivity in the second half of the century. Compared to no management, the other options had a moderate effect on carbon fluxes over the whole simulation (between -14 % and +11 %). While standing woody biomass was reduced by thinning interventions and the shelterwood system (between -5 % and -41 %), overall carbon stocks including the harvested wood were maximized (between +41 % and +56 %). Results highlight that management exerts greater effects on the carbon budget of Laricio pine plantations than climate change alone, and that climate change and management are largely independent (i.e., no strong interaction effects). Therefore, appropriate silvicultural strategies might enhance potential carbon stocks and improve forest conditions, with cascading positive effects on the provision of ecosystem services in Mediterranean pine plantations.

Accuracy, realism and general applicability of European forest models.

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.