(12) , D Morresi (12) , M Garbarino (12) , G Alberti (13) , F Valdevit (13) , E Tomelleri (14) , M Torresani (14) , G Tonon (14) , M Marchi (15) , P Corona (15) , M Marchetti (16) Forest damage inventory after the "Vaia" storm in Italy On October 29, 2018, the Vaia storm hits the NorthEastern 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

Context Since the nineteenth century, rural areas have experienced progressive abandonment mostly due to socioeconomic changes, with direct and indirect effects on forest disturbance regimes occurring in these human-dominated landscapes. The role of land abandonment in modifying disturbance regimes has been highlighted for some types of disturbances, albeit being still somewhat overlooked compared to climate change. Objectives This literature review is aimed at highlighting the most relevant effects of land abandonment and land-use legacy on the regime of different types of forest disturbances, providing insight into land-use change/disturbances interactions. Methods We searched in the Scopus and Web of Science databases for relevant studies at the global scale dealing with eight major natural disturbances: avalanche, flooding, herbivory, insect outbreak, landslide, rockfall, wildfire and windthrow. We classified papers into five relevance classes, with the highest score (4) assigned to studies quantitatively measuring the interactions between abandonment dynamics and disturbance regimes. Results Most papers focused on wildfires in Mediterranean Europe in the twentieth century, where landscape homogenisation and fuel build-up contributed to worsening their frequency, size and severity. Dense forests developed following land abandonment instead exert inhibiting effects toward mass movements such as avalanches, rockfalls and landslides. Regarding the other investigated disturbances, we found only a few studies presenting site-specific and partly contrasting effects. Conclusions Land abandonment triggers ecological processes at the landscape scale, altering land cover patterns and vegetation communities, which in turn affect disturbance regimes. Implications for land and resource management mostly depend on the stage at which post-abandonment secondary succession has developed.

Understanding post-fire regeneration dynamics is an important task for assessing the resilience of forests and to adequately guide post-disturbance management. The main goal of this research was to compare the ability of different Landsat-derived spectral vegetation indices (SVIs) to track post-fire recovery occurring in burned forests of the central Apennines (Italy) at different development stages. Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Burn Ratio (NBR), Normalized Burn Ratio 2 (NBR2) and a novel index called Forest Recovery Index 2 (FRI2) were used to compute post-fire recovery metrics throughout 11 years (2008–2018). FRI2 achieved the highest significant correlation (Pearson’s r = 0.72) with tree canopy cover estimated by field sampling (year 2017). The Theil–Sen slope estimator of linear regression was employed to assess the rate of change and the direction of SVIs recovery metrics over time (2010–2018) and the Mann–Kendall test was used to evaluate the significance of the spectral trends. NDVI displayed the highest amount of recovered pixels (38%) after 11 years since fire occurrence, whereas the mean value of NDMI, NBR, NBR2, and FRI2 was about 27%. NDVI was more suitable for tracking early stages of the secondary succession, suggesting greater sensitivity toward non-arboreal vegetation development. Predicted spectral recovery timespans based on pixels with a statistically significant monotonic trend did not highlight noticeable differences among normalized SVIs, suggesting similar suitability for monitoring early to mid-stages of post-fire forest succession. FRI2 achieved reliable results in mid- to long-term forest recovery as it produced up to 50% longer periods of spectral recovery compared to normalized SVIs. Further research is needed to understand this modeling approach at advanced stages of post-fire forest recovery.

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Context: Land use legacies of human activities and recent post-abandonment forest expansion have extensively modified numerous forest landscapes throughout the European mountain ranges. Drivers of forest expansion and the effects of changes on ecosystem services are currently debated.Objectives: i) to compare landscape transition patterns of the Alps and the Apennines (Italy), ii) to quantify the dominant landscape transitions, and iii) to measure the influence of climatic, topographic and anthropogenic driving factors.Methods: Land cover changes and landscape pattern modifications were investigated at the regional (over 28 years, Alps and Apennines, Corine Land Cover dataset) and landscape scale (over 58 years, 8 Alpine and 8 Apennine sites, aerial images). The main driving factors of post-abandonment forest landscape dynamics were assessed with a statistical modeling approach.Results: Forest expansion was the dominant landscape transition at both Italian mountain ranges, with an annual overall rate of 0.6%. Forest expansion was more extensive at lower elevations in the Apennines where climate is less limiting and extensive abandoned croplands and pastures were available throughout the study period. Distance from pre-existing forest edges in the Alps and elevation in the Apennines emerged as the most important predictors.Conclusions: Forest expansion is most rapid where areas of recent agricultural abandonment coincide with favorable climatic conditions. Thus the prediction of forest landscape dynamics, in these mountain forests with a long history of cultural use, requires knowledge of how the magnitude and timing of land use changes intersect spatially and temporally with suitable conditions for tree establishment and growth.

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The increase of wildfire incidence in highly populated areas significantly enhances the risk for ecosystems and human lives, activities and infrastructures. In central and southern Italy, recent decades’ fire records indicate that 2007 and 2017 were extreme years in terms of the number of fires and total burned area. Among them, we selected large fire events and explored their features and drivers of burn severity. We used a standardized extraction procedure to identify large wildfires (>100 ha) from the MODIS burned areas database and Landsat multi-spectral images. We mapped burn severity with the Relative Difference Normalized Burn Ratio index and explored the main drivers of severity using topographic, land-cover and anthropogenic predictors. We selected 113 wildfires for a collective total burned area of over 100,000 ha. Large fires were more frequent in the southern than in the central and northern regions, especially in July and August. The average fire size was about 900 ha and occurred mainly in shrublands (30.4%) and broadleaf forests (19.5%). With a random forest model, we observed that the highest severity occurred in conifer plantations and shrublands, in highly populated areas and at lower elevations. Burn severity models, at the landscape or regional scales, can be very useful tools for pre- and post-fire forest management planning.

Background The Mediterranean basin is currently facing major changes in fire regimes as a result of climate and land-use changes. These alterations could affect the ability of forests to recover after a fire, hence triggering degradation processes and modifying the provision of fundamental ecosystem services. Examining patterns and drivers of post-fire forest recovery, particularly for obligate seeders without specific fire-adaptive traits, thus becomes a priority for researchers and land managers. We studied the post-fire dynamics of Scots pine (Pinus sylvestris L.) stands affected by a mixed-severity fire in North-Western Italy, aiming to understand the impact of fire on soil properties and assess drivers, spatial distribution, and characteristics of short-term post-fire recovery. Results We observed that fire did not significantly affect soil organic carbon (OC) content, while we detected significantly lower nitrogen (N) content in severely burnt sites. Regeneration density was particularly abundant in medium-severity areas, while it drastically decreased in high-severity patches. The most abundant tree species in the regeneration layer was Scots pine, followed by goat willow (Salix caprea L.), European aspen (Populus tremula L.), and, to a lesser extent, European larch (Larix decidua Mill.). Slope, fire severity, and distance from seed trees emerged as the most important drivers of post-fire forest regeneration patterns. Conclusions Our results highlight the importance of preserving seed trees from salvage logging, even if they are damaged and have a low survival probability. Active post-fire management, such as tree planting, should be limited to large and severely burnt patches, where natural forest regeneration struggles to settle, increasing the risk of ecosystem degradation. These findings could be useful for informing land managers, helping them to enhance potential mitigation strategies in similar ecosystems and plan appropriate restoration approaches.