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On October 29, 2018, the Vaia storm hits the North-Eastern regions of Italy by wind gusts exceeding 200 km h-1. The forests in these regions have been seriously damaged. This contribution illustrates the methodology adopted in the emergency phase to estimate forest damages caused by Vaia storm, both in terms of damaged forest areas and growing stock volume of fallen trees. 494 Municipalities registered forest damages caused by Vaia, destroyed or intensely damaged forest stands amounted to about 42.500 ha, spread in Trentino Alto Adige, Veneto, Friuli Venezia Giulia, Lombardy and, only marginally, Piedmont and Valle d’Aosta. The growing stock volume of fallen trees was about 8.5 millions m3.

Laser scanning is a recently-introduced remote sensing technology that shows high potentiality in the context of the forestry resources management. The research group of the University of Udine, within an INTERREG IIIA Phare/CBC Italy-Slovenia project, developed specific methods regarding the use of LiDAR data for forestry applications. A specific methodology which makes possible to obtain the position of the single trees and their relative heights has been implemented. On the basis of the height distributions, using stand height curves relation already available in the stand volume tables, a method to derive the volume values of each tree is proposed. The paper shows the first results obtained with the above method in terms of diameter and volume estimation on the basis of laser scanning data surveyed in different composed forestry plots. A comparison between laser-based and traditional methods-based data is also presented. Some of the consequences of this different way to use the stand volume tables were analyzed, and an experimental procedure is proposed that seems to guarantee a sufficient reliability of the results, and their historical continuity. Furthermore, the approach described may reduce the costs of the traditional dendrometric assessment, nowadays not sustainable in forest management.

Aboveground biomass, increment and carbon stock in a 36 forest plantations chronosequence of different ages were quantified. Results have been extrapolated in time using the Richard’s model. Maximum carbon stock was measured in 23 years old plantations (37 tC ha-1) and annual carbon stock rate occurs at 9 years (3.4 tC ha-1 year-1). After this age it decreases to reach 0.40 tC ha-1 year-1 at 23 years after plantation.

The forest communities distribution in mountainous areas is strongly related to some primary ecological factors (e.g., water, temperature, geology) and to some other factors derived from the soil morphology (e.g., slope, aspect and solar radiation). The aim of this study is to investigate and express quantitatively the relationships between ecological factors and forest communities through geospatial analysis in a GRASS GIS. There are significant statistical differences between forest communities according to environmental factors (Kruskal-Wallis test, T2 of Tamhane, PCA). Some ecological factors studied (e.g., solar potential radiation) are useful to describe forest communities in indirect gradient analysis. The study area is located in the Eastern Prealps of Friuli Venezia Giulia (Italy) and is characterized by a large environmental variability (climate, natural and human disturbances).