Past failures of monocultures, caused by wind-throw or insect damages, and ongoing climate change currently strongly stimulate research into mixed-species stands. So far, the focus has mainly been on combinations of species with obvious complementary functional traits. However, for any generalization, a broad overview of the mixing reactions of functionally different tree species in different mixing proportions, patterns and under different site conditions is needed, including assemblages of species with rather similar demands on resources such as light. Here, we studied the growth of Scots pine and oak in mixed versus monospecific stands on 36 triplets located along a productivity gradient across Europe, reaching from Sweden to Spain and from France to Georgia. The set-up represents a wide variation in precipitation (456–1250 mm year⁻¹), mean annual temperature (6.7–11.5 °C) and drought index by de Martonne (21–63 mm °C⁻¹). Stand inventories and increment cores of trees stemming from 40- to 132-year-old, fully stocked stands on 0.04–0.94-ha-sized plots provided insight into how species mixing modifies stand growth and structure compared with neighbouring monospecific stands. On average, the standing stem volume was 436 and 360 m³ ha⁻¹in the monocultures of Scots pine and oak, respectively, and 418 m³ ha⁻¹in the mixed stands. The corresponding periodical annual volume increment amounted to 10.5 and 9.1 m³ ha⁻¹ year⁻¹in the monocultures and 10.5 m³ ha⁻¹ year⁻¹in the mixed stands. Scots pine showed a 10% larger quadratic mean diameter (p < 0.05), a 7% larger dominant diameter (p < 0.01) and a 9% higher growth of basal area and volume in mixed stands compared with neighbouring monocultures. For Scots pine, the productivity advantages of growing in mixture increased with site index (p < 0.01) and water supply (p < 0.01), while for oak they decreased with site index (p < 0.01). In total, the superior productivity of mixed stands compared to monocultures increased with water supply (p < 0.10). Based on 7843 measured crowns, we found that in mixture both species, but especially oak, had significantly wider crowns (p < 0.001) than in monocultures. On average, we found relatively small effects of species mixing on stand growth and structure. Scots pine benefiting on rich, and oak on poor sites, allows for a mixture that is productive and most likely climate resistant all along a wide ecological gradient. We discuss the potential of this mixture in view of climate change.

The paper provides a detailed overview on forest models from various perspectives. The presented classification scheme of forest models uses concept, object, space and time as variables to place models in specific categories and thus provides an integrated approach for model categorisation. A short description of individual categories with the examples of models helps to understand their nature. In total 34 forest models were classified according to the created scheme. Forest visualisation has also an important place in forest modelling. Here it is described from the point of different visualisations methods and used technologies. Inputs that are necessary for the models but are often not available and need to be derived using specialised tools – various forms of data generators are presented too. Important perspectives and challenges of further development of forest models and visualisation technologies were specified as well.

The crown architecture and structural growth strongly affect the total volume and biomass of Norway spruce trees at a specific age. The main objective of this study was to explore the branching strategy of young spruce trees growing in a highly-dense naturally regenerated forest stand. The level of branching described by the Gravelius order of the growth units, as well as the unit’s branching direction and angles were analyzed. The significant factors that influence the occurrence frequency of growth units were the branching order and their life status. The results manifested the highest frequency of growth units in the first and second order in given conditions. A significant association between the branching direction of the mother unit and the first successive growth unit of higher order was revealed. Also, the mean branching angles were influenced by the branching order and relative position of the growth unit in relation to the mother unit. The branching angle distributions were left-skewed and the angles varied between 40° and 70°. The results improve our understanding of structural development of spruce crowns and can contribute to more realistic modeling of biomass production using tree growth simulators.

The main objective of this study was to explore the accuracy of Weise’s rule of thumb applied to an estimation of the quadratic mean diameter of a forest stand. Virtual stands of European beech (Fagus sylvatica L.) across a range of structure types were stochastically generated and random sampling was simulated. We compared the bias and accuracy of stand quadratic mean diameter estimates, employing different ranks of measured stems from a set of the 10 trees nearest to the sampling point. We proposed several modifications of the original Weise’s rule based on the measurement and averaging of two different ranks centered to a target rank. In accordance with the original formulation of the empirical rule, we recommend the application of the measurement of the 6th stem in rank corresponding to the 55% sample percentile of diameter distribution, irrespective of mean diameter size and degree of diameter dispersion. The study also revealed that the application of appropriate two-measurement modifications of Weise’s method, the 4th and 8th ranks or 3rd and 9th ranks averaged to the 6th central rank, should be preferred over the classic one-measurement estimation. The modified versions are characterised by an improved accuracy (about 25%) without statistically significant bias and measurement costs comparable to the classic Weise method.

Augmented reality (AR) offers several advantages in the commercialization of wood products, increasing both the efficiency and the attractiveness of the process of presenting and selling them. The digitization and virtualization of wood features/products for the purpose of their economic valorization represent a significant advance in technology and its application in traditional industries such as wood processing and trade. We present a concrete process of digitization and virtualization of wood features through AR for the purpose of its commercial valorization. Three methods of object scanning are tested: convergent photogrammetry, LiDAR scanning using an iPhone, and handheld scanners. Wood samples with different textures, shapes, and surface properties were used for the research, while each method was tested on a trio of models. The methods showed specific limitations: convergent photogrammetry is time-consuming and prone to human error, LiDAR iPhone scanning provides lower output quality and struggles with reflective surfaces, while handheld scanners are expensive and require additional tools for capturing color. Convergent photogrammetry was evaluated as the optimal and available method for the widest range of users. The 3D models were integrated into the Virtual Wood Market application, created in the Unreal Engine environment. The use of augmented reality in wood product commercialization offers significant benefits, including enhanced material efficiency, improved design and fabrication processes, better supply chain management, and increased customer engagement. These advantages can lead to more sustainable practices and higher customer satisfaction, ultimately driving the success of wood product commercialization.