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Fire is a major disturbance that affects ecological communities, and when fire events increase in frequency or extent, they may jeopardise biodiversity. Although long-term studies are irreplaceable to understand how biological communities respond to wildfires, a rapid, efficient assessment of the consequences of wildfire is paramount to inform habitat management and restoration. Although Species Distribution Models (SDMs) may be applied to achieve this goal, they have not yet been used in that way. In summer 2017, during an extended drought that affected Italy, a severe wildfire occurred in the Vesuvius National Park (southern Italy). We applied SDMs to assess how much potential habitat was lost by the 12 bat species occurring in the area because of the wildfire, and whether habitat fragmentation increased following the event. Our analysis supported the hypotheses we tested (i.e. that the fire event potentially affected all species through habitat reduction and fragmentation) and that the bat species potentially most affected were those adapted to foraging in cluttered habitat (forest). We show that SDMs are a valuable tool for a first, rapid assessment of the effects of large-scale wildfires, and that they may help identify the areas that need to be monitored for animal activity and phenology, and to assist in saving human and financial resources.

Physical and chemical properties and the total content of potentially toxic metals (PTMs) in waters and soils were studied from the High Moulouya Valley (Morocco) in order to assess the impact of the past mining activity on their quality and to lay the foundations of a potential reclamation of the area. Surface water and groundwater samples were collected from the Moulouya River and mine pit lakes; tailings and soils were sampled inside and outside the mine sites of Ze < da, Mibladen, and Aouli. Both waters and soils were alkaline, due to the limestone environment, and contained Pb and Zn as main metallic contaminants. Pollution levels were highest within the Mibladen mining site, and soil pollution was mainly restricted to the areas where activities of metal concentration were carried out. Tailings and soils from these areas besides Pb and Zn were also polluted by As, Cd, and Cu showing clay fraction highly enriched in metal contaminants. At the time of study, all soils and wastes (including the highly polluted tailings) were in advanced stage of spontaneous herbaceous and arbustive revegetation. It is concluded that, in the High Moulouya Valley, the processes governing PTM transfer from the element-rich sites to the nearby environment are strongly influenced by pH, carbonate content, and semi-arid climate reducing metal mobility from the mining waste impoundments by dissolution. The transfer by wind and water erosion of metal-enriched fine waste particles is likely to be a much more important vector for metal dispersion. In this perspective, among a range of land remediation techniques available, natural and oriented revegetation could represent a low-cost and possible permanent solution

In Mediterranean countries, in the year 2017, extensive surfaces of forests were damaged by wildfires. In the Vesuvius National Park, multiple summer wildfires burned 88% of the Mediterranean forest. This unprecedented event in an environmentally vulnerable area suggests conducting spatial assessment of the mixed-severity fire effects for identifying priority areas and support decision-making in post-fire restoration. The main objective of this study was to compare the ability of the delta Normalized Burn Ratio (dNBR) spectral index obtained from Landsat-8 and Sentinel-2A satellites in retrieving burn severity levels. Burn severity levels experienced by the Mediterranean forest communities were defined by using two quali-quantitative field-based composite burn indices (FBIs), namely the Composite Burn Index (CBI), its geometrically modified version CBI (GeoCBI), and the dNBR derived from the two medium-resolution multispectral remote sensors. The accuracy of the burn severity map produced by using the dNBR thresholds developed by Key and Benson (2006) was first evaluated. We found very low agreement (0.15 < K < 0.21) between the burn severity class obtained from field-based indices (CBI and GeoCBI) and satellite-derived metrics (dNBR) from both Landsat-8 and Sentinel-2A. Therefore, the most appropriate dNBR thresholds were rebuilt by analyzing the relationships between two field-based (CBI and GeoCBI) and dNBR from Landsat-8 and Sentinel-2A. By regressing alternatively FBIs and dNBRs, a slightly stronger relationship between GeoCBI and dNBR metrics obtained from the Sentinel-2A remote sensor (R2 = 0.69) was found. The regressed dNBR thresholds showed moderately high classification accuracy (K = 0.77, OA = 83%) for Sentinel-2A, suggesting the appropriateness of dNBR-Sentinel 2A in assessing mixed-severity Mediterranean wildfires. Our results suggest that there is no single set of dNBR thresholds that are appropriate for all burnt biomes, especially for the low levels of burn severity, as biotic factors could affect satellite observations.

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