Diameter, height and species of 42 million trees in three European landscapes generated from field data and airborne laser scanning data.

Ecology and forestry sciences are using an increasing amount of data to address a wide variety of technical and research questions at the local, continental and global scales. However, one type of data remains rare: fine-grain descriptions of large landscapes. Yet, this type of data could help address the scaling issues in ecology and could prove useful for testing forest management strategies and accurately predicting the dynamics of ecosystem services. Here we present three datasets describing three large European landscapes in France, Poland and Slovenia down to the tree level. Tree diameter, height and species data were generated combining field data, vegetation maps and airborne laser scanning (ALS) data following an area-based approach. Together, these landscapes cover more than 100 000 ha and consist of more than 42 million trees of 51 different species. Alongside the data, we provide here a simple method to produce high-resolution descriptions of large landscapes using increasingly available data: inventory and ALS data. We carried out an in-depth evaluation of our workflow including, among other analyses, a leave-one-out cross validation. Overall, the landscapes we generated are in good agreement with the landscapes they aim to reproduce. In the most favourable conditions, the root mean square error (RMSE) of stand basal area (BA) and mean quadratic diameter (Dg) predictions were respectively 5.4 m 2.ha -1 and 3.9 cm, and the generated main species corresponded to the observed main species in 76.2% of cases.

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.

The Salem simulator version 2.0: a tool for predicting the productivity of pure and mixed forest stands and simulating management operations.

A growing body of research suggests mixed-species stands are generally more productive than pure stands as well as less sensitive to disturbances. However, these effects of mixture depend on species assemblages and environmental conditions. Here, we present the Salem simulator, a tool that can help forest managers assess the potential benefit of shifting from pure to mixed stands from a productivity perspective. Salem predicts the dynamics of pure and mixed even-aged stands and makes it possible to simulate management operations. Its purpose is to be a decision support tool for forest managers and stakeholders as well as for policy makers. It is also designed to conduct virtual experiments and help answer research questions. In Salem, we parameterised the growth in pure stand of 12 common tree species of Europe and we assessed the effect of mixture on species growth for 24 species pairs (made up of the 12 species mentioned above). Thus, Salem makes it possible to compare the productivity of 36 different pure and mixed stands depending on environmental conditions and user-defined management strategies. Salem is essentially based on the analysis of National Forest Inventory data. A major outcome of this analysis is that we found species mixture most often increases species growth, in particular at the poorest sites. Independently from the simulator, foresters and researchers can also consider using the species-specific models that constitute Salem: the growth models including or excluding mixture effect, the bark models, the diameter distribution models, the circumference-height relationship models, as well as the volume equations for the 12 parameterised species. Salem runs on Windows, Linux, or Mac. Its user-friendly graphical user interface makes it easy to use for non-modellers. Finally, it is distributed under a LGPL license and is therefore free and open source.

Carbon costs and benefits of France's biomass energy production targets.

BACKGROUND: Concern about climate change has motivated France to reduce its reliance on fossil fuel by setting targets for increased biomass-based renewable energy production. This study quantifies the carbon costs and benefits for the French forestry sector in meeting these targets. A forest growth and harvest simulator was developed for French forests using recent forest inventory data, and the wood-use chain was reconstructed from national wood product statistics. We then projected wood production, bioenergy production, and carbon balance for three realistic intensification scenarios and a business-as-usual scenario. These intensification scenarios targeted either overstocked, harvest-delayed or currently actively managed stands. RESULTS: All three intensification strategies produced 11.6-12.4 million tonnes of oil equivalent per year of wood-based energy by 2026, which corresponds to the target assigned to French wood-energy to meet the EU 2020 renewable energy target. Sustaining this level past 2026 will be challenging, let alone further increasing it. Although energy production targets can be reached, the management intensification required will degrade the near-term carbon balance of the forestry sector, compared to continuing present-day management. Even for the best-performing intensification strategy, i.e., reducing the harvest diameter of actively managed stands, the carbon benefits would only become apparent after 2040. The carbon balance of a strategy putting abandoned forests back into production would only break even by 2055; the carbon balance from increasing thinning in managed but untended stands would not break even within the studied time periods, i.e. 2015-2045 and 2046-2100. Owing to the temporal dynamics in the components of the carbon balance, i.e., the biomass stock in the forest, the carbon stock in wood products, and substitution benefits, the merit order of the examined strategies varies over time. CONCLUSIONS: No single solution was found to improve the carbon balance of the forestry sector by 2040 in a way that also met energy targets. We therefore searched for the intensification scenario that produces energy at the lowest carbon cost. Reducing rotation time of actively managed stands is slightly more efficient than targeting harvest-delayed stands, but in both cases, each unit of energy produced has a carbon cost that only turns into a benefit between 2060 and 2080.

Assessing the effects of management on forest growth across France: insights from a new functional-structural model.

BACKGROUND AND AIMS: The structure of a forest stand, i.e. the distribution of tree size features, has strong effects on its functioning. The management of the structure is therefore an important tool in mitigating the impact of predicted changes in climate on forests, especially with respect to drought. Here, a new functional-structural model is presented and is used to assess the effects of management on forest functioning at a national scale. METHODS: The stand process-based model (PBM) CASTANEA was coupled to a stand structure module (SSM) based on empirical tree-to-tree competition rules. The calibration of the SSM was based on a thorough analysis of intersite and interannual variability of competition asymmetry. The coupled CASTANEA-SSM model was evaluated across France using forest inventory data, and used to compare the effect of contrasted silvicultural practices on simulated stand carbon fluxes and growth. KEY RESULTS: The asymmetry of competition varied consistently with stand productivity at both spatial and temporal scales. The modelling of the competition rules enabled efficient prediction of changes in stand structure within the CASTANEA PBM. The coupled model predicted an increase in net primary productivity (NPP) with management intensity, resulting in higher growth. This positive effect of management was found to vary at a national scale across France: the highest increases in NPP were attained in forests facing moderate to high water stress; however, the absolute effect of management on simulated stand growth remained moderate to low because stand thinning involved changes in carbon allocation at the tree scale. CONCLUSIONS: This modelling approach helps to identify the areas where management efforts should be concentrated in order to mitigate near-future drought impact on national forest productivity. Around a quarter of the French temperate oak and beech forests are currently in zones of high vulnerability, where management could thus mitigate the influence of climate change on forest yield.