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.

Regional height growth models for Scots pine in Poland.

Site productivity remains a fundamental concern in forestry as a significant driver of resource availability for tree growth. The site index (SI) reflects the overall impact of all environmental factors that determine tree height growth and is the most commonly used indirect proxy for forest site productivity estimated using stand age and height. The SI concept challenges are local variations in climate, soil, and genotype-environmental interactions that lead to variable height growth patterns among ecoregions and cause inappropriate estimation of site productivity. Developing regional models allow us to determine forest growth and SI more appropriately. This study aimed to develop height growth models for the Scots pine in Poland, considering the natural forest region effect. For height growth modelling, we used the growth trajectory data of 855 sample trees, representing the Scots pine entire range of geographic locations and site conditions in Poland. We compared the development of regional height growth models using nonlinear-fixed-effects (NFE) and nonlinear-mixed-effects (NME) modelling approaches. Our results indicate a slightly better fit to the data of the model built using NFE approach. The results showed significant differences between Scots pine growth in natural forest regions I, II, and III located in northern Poland and natural forest regions IV, V, and VI in southern Poland. We compared the development of regional height growth models using NFE and NME modelling approaches. Our results indicate a slightly better fit to the data of the model built using the NFE approach. The developed models show differences in height growth patterns of Scots pines in Poland and revealed that acknowledgement of region as the independent variable could improve the growth prediction and quality of the SI estimation. Differences in climate and soil conditions that distinguish natural forest regions affect Scots pine height growth patterns. Therefore, extending this research to models that directly describe height growth interactions with site variables, such as climate, soil properties, and topography, can provide valuable forest management information.

Tree height as the main factor causing disappearance of the terricolous lichens in the lichen Scots pine forests.

The lichen Scots pine forests habitats are undergoing rapid disappearance across Europe. Due to the semi-natural character of this habitat and an increase of the nitrification as a result of air pollution, determination of factors responsible for the decrease in lichen field layer cover requires a comprehensive approach. Our study aimed to investigate environmental factors necessary for the determination of active protection measures in order to maintain this vulnerable habitat. Specifically, we aimed to investigate: 1) the environmental factors influencing lichen cover in the lichen Scots pine forests of Bory Tucholskie National Park; 2) the differences in habitat variables between sites with lichen-rich and bryophyte-rich field layers. In our study, we used vegetation and microhabitat properties data collected over three years of surveys, as well as ALS LiDAR data. Our results indicated that lichen and bryophyte cover, tree height, tree cover, thickness of organic matter layer, soil temperature and soil water content differed between lichen-rich and bryophyte-rich sites. We found a significant negative relationship between lichen cover recorded within the field layer and tree height. The lichen-rich field layer developed better in areas with lower tree height and thinner layer of organic matter, which created a favorable habitat conditions for lichen development. Our research revealed the previously unknown impact of tree height for the development of lichen field layer. These findings can be used to plan the active conservation measures of lichen Scots pine forests.