Background: Wildfires are increasingly impacting ecosystems worldwide especially in temperate dry habitats, often interplaying with other global changes (e.g., alien plant invasions). Understanding the ecological consequences of wildfires is crucial for effective conservation and management strategies. The aim of this study was to investigate the impacts of wildfire severity on plant community (both the canopy trees and herbaceous layer) and alien plant invasion, combining field observations and remotely sensed data. We conducted an observational study in the Karst forests (North-East Italy) 1 year after the large wildfire which affected the area in 2022. We assessed the impact through 35 field plots (200 m² each) distributed among different fire severity (i.e., the loss of organic matter) classes assessed using the differenced normalized burn ratio (dNBR) calculated from satellite images. In each plot, tree species, diameter, vitality, resprouting capacity, and seedling density were measured. In addition, herb species richness (taxonomical diversity) was quantified, and plant cover was visually estimated. Functional diversity was also assessed considering six functional traits retrieved from databases. Results: Some woody species (e.g., Quercus pubescens) showed a higher resistance to the fire (i.e., lower mortality rate), while others showed a higher resilience (i.e., recovery after fire through resprouting or seedlings, e.g., Cotinus coggygria). The transition to a shrub-dominated community (i.e., Cotinus coggygria) where fire severity was the highest underlines the dynamic nature of the post-fire succession. We detected a significant variation in the herbaceous plant community composition, diversity, and functional identity (i.e., community-weighted mean of trait) along the fire severity gradient. In particular, high-fire severity areas exhibited higher species richness compared to low-severity or unburned areas. Total alien plant cover increased with fire severity, while native cover remained constant. We also found shifts in species that enhance traits related to germination potential and growth strategy. Conclusions: Our results highlight the vulnerability of the forest stands to an increase in wildfire severity, resulting in significant mortality and changes in tree community structure. This study contributes to the understanding of ecological processes after wildfires using a novel remote sensing approach in a temperate forest, emphasizing the need for conservation strategies aimed at mitigating high severity wildfires.

The role of forests in providing multiple goods and services has been recognized worldwide. In such a context, reliable spatial predictions of forest attributes such as tree volume and current increment are fundamental for conducting forest monitoring, improving restoration programs, and supporting decision-making processes. This article presents the methodology and the results of the wall-to-wall spatialization of the growing stock volume and the current annual increment measured in 273 plots of data of the Italian National Forest Inventory over an area of more than 3260 km² in the Friuli Venezia Giulia region (Northeast Italy). To this aim, a random forest model was tested using as predictors 4 spectral indices from Sentinel-2, a high-resolution Canopy Height Model derived from LiDAR, and geo-morphological data. According to the Leave One Out cross-validation procedure, the model for the growing stock shows an R² and an RMSE% of 0.67 and 41%, respectively. Instead, an R² of 0.47 and an RMSE% of 57% were obtained for the current annual increment. The validation with an independent dataset further improved the models’ performances, yielding significantly higher R² values of 0.84 and 0.83 for volume and for increment, respectively. Our results underline a relatively higher importance of LiDAR-derived metrics compared to other covariates in estimating both attributes, as they were even twice as important as vegetation indices for growing stock. Therefore, these metrics are promising for the development of a national LiDAR-based model.

One of the most important obstacles for taking advantage of forest resources in the Italian Alps is represented by the high level of private properties fragmentation and by their small size. Thus, there is an urgent need for tools to support single or multi-forest owners to gain reliable and updated information on their forest stands so that the proper silvicultural activities following all the existing regulations can be adopted. The present research was aimed at promoting a shared management of small private forest properties in the mountainous area of Friuli Venezia Giulia (NE Italy) through the implementation of a new WebGIS tool to support forest decisions and management at different spatial scales. This new tool was developed updating and merging together different available information sources (e.g., tree species composition, the presence of protected areas, forest roads, etc.) with ad-hoc elaborated layers (e.g., standing volume, annual increment of volume, forest accessibility, etc.), also elaborating a cost analysis related to the different possible harvesting methods. The tool allows queries at the level of either a single or a group of cadastral parcels to obtain data in a format, which can be used for filling in the planning document requested by the regional authorities.

After stand-replacing windstorm salvage logging is the most common practice for recovering economic losses in managed forests and for reducing the risk of subsequent disturbances (e.g. bark beetle outbreaks). To restore forest cover timely after these interventions is therefore necessary, in order to limit the reduction of forest ecosystem services (ES) provision. In the first years following the disturbance and subsequent interventions, there is a need to monitor natural regeneration dynamics in damaged areas, in order to implement active restoration activities if necessary. In this study, we analyze the natural regeneration dynamics in 148 areas damaged by storm Vaia (2018) and salvage logged with different techniques in Northeast of Italy. Results show that regeneration species composition is driven mainly by previous stand composition, with some exceptions depending on seed dispersal strategy. Distance from the edge significantly influences the regeneration occurrence in large gaps and affects the browsing damage percentage, together with deadwood presence. Moreover, site factors, disturbance legacies, and logging methods reveal to be key points to consider in the post-disturbance management strategies definition. To reduce economic losses and exploit the windthrown areas in the short-term, it is possible to integrate reforestation with agroforestry practices (e.g. berries and honey production). This is the framework of the LIFE VAIA project, which aims to integrate innovative local agroforestry practices with artificial regeneration to restore forest cover, increasing the value of forest ecosystems and the ecological and socio-economical resilience of damaged forest ecosystems under future climate changes.