Windstorms represent one of the main large-scale disturbances that shape the European landscape and influence its forest structure, so post-event restoration activities start to gain a major role in mountainous forest management. After a disturbance event, biological legacies may enhance or maintain multiple ecosystem services of mountain forests such as protection against natural hazards, biodiversity conservation, or erosion mitigation. However, the conservation of all these ecosystem services after stand-replacing events could go against traditional management practices, such as salvage logging. Thus far, the impact of salvage logging and removal of biological legacies on the protective function of mountain stands has been poorly studied. Structural biological legacies may provide protection for natural regeneration and may also increase the terrain roughness providing a shielding effect against gravitational hazards like rockfall. The aim of this project is to understand the dynamics of post-windthrow recovery processes and to investigate how biological legacies affect the multifunctionality of mountain forests, in particular the protective function. To observe the role of biological legacies we performed 3000 simulations of rockfall activity on windthrown areas. Results show the active role of biological legacies in preventing gravitational hazards, providing a barrier effect and an energy reduction effect on rockfall activity. To conclude, we underline how forest management should take into consideration the protective function of structural legacies. A suggestion is to avoid salvage logging in order to maintain the multifunctionality of damaged stands during the recovery process.
23 September 2022 in Forest Ecology and Management
Purpose of the Review: We aim to present virtual forest visualization in an accessible manner to help a broad audience understand this concept along with spatial data integration to create digital environments that closely replicate real-world forests. Such efforts are motivated by a multitude of reasons, from creating a virtual science laboratory to guiding real-world applications. The digital reconstruction of forests is an evolving field in forestry, with close connections to computer science and data science. The key considerations in visualization are also explained in detail which are crucial part of visualization like Input and output data along with challenges and constraints. Findings: Recent advancements in digital sensing technologies have improved forest visualizations considerably. Data from techniques such as LiDAR and photogrammetry, along with other forest information, have facilitated the creation of highly detailed and accurate virtual forest models. These technologies not only capture the geometric structure of forests, but also enable the interactive exploration of different layers, from the canopy to the forest floor. The integration of these methods with Geographic Information Systems (GIS) and various user interfaces has further enhanced the spatial accuracy and contextual relevance of virtual forests. A major breakthrough in forest visualization is the incorporation of Extended Reality (XR) technologies, including Augmented (AR), Virtual (VR), and Mixed Reality (MR). These tools enable users to experience forest environments in a fully immersive way, without the need for physical presence. Given that some forests are prohibitively difficult to reach and navigate, and that some experiences can be greatly enriched by overlaying virtual elements onto the real world, XR experiences offer a valuable alternative to traditional data visualization approaches. Additionally, we also present four case studies to showcase the applications of visualization in the European forest context which can be applicable in the global context. Summary: We examine key trends, developments, and challenges according to the global research in the use of 2D and 3D visualization for virtual forest experiences and present selected case studies. We describe the potential of virtual forest visualization for applications in forest management, conservation, education, and research. We also present an opportunity to utilize and develop further the scope of visualization using these latest technologies in forestry globally.
Climate change will increase the frequency and magnitude of extreme meteorological events. Therefore, also windstorm events are expected to increase the amount of damages to natural and human resources. Regarding forests, windstorms are already the first cause of timber damages in Europe. In such sense, it is crucial to predict the vulnerability of forest stands and in this direction, different stochastic and statistical models have been developed and successfully tested on real events. To improve the resistance of forests against windstorms it is also necessary to forecast the future probability of damage (i.e. 100 years scenario) taking into account the changes in the characteristics of the forest cover as species composition, density, stand height, etc. In this way, forest managers can delineate specific silviculture operations in order to obtain more wind-resistant forests in a climate change context. In this study, we simulated the changes in the forest cover due to climate change and past natural events that affected the forest structure through the use of a dynamic vegetation model (e.g. TreeMig). The outcomes of the model are directly transferred to the wind susceptibility model in order to compute the probable critical wind speeds of overturning and breakage. The proposed methodology is applied to the municipality area of Rocca Pietore (74 km2 of which half covered by forest), north eastern Italian Alps. The input data for the forest model are semi-automatically generated by a LiDAR survey while for the climate data high resolution CHELSA dataset has been used. The outputs are post-processed and passed to the wind risk model ForestGALES. The outputs (derived at a fine scale) show the variation in wind vulnerability in accordance with the changes of the forest characteristics. The methodology proposed in this study produce future windthrow vulnerability maps. Consequently, forest managers could quickly identify areas that can be at high risk and test alternative scenarios to increase the stand resistance.