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Surface biomass characterization plays a key role in wildfire management. It allows classifying vegetation fuels flammability for fire risk analysis, to define silvicultural prescriptions for fire hazard reduction, to plan prescribed burning, or to model fire behavior and its effects, such as greenhouse gas and pollutant emissions. To facilitate fuel classification and analysis of potential fire behavior and effects in Italy, we harmonized 634 measurements of surface wildland fuels from Alpine, temperate and Mediterranean environments. The dataset provides quantitative data for duff, fine dead fuels and downed woody material, live grasses and shrubs fuel components. Surface fuel data were harmonized by subdividing loads (Mg ha-1) to standard size classes for dead (0-6, 6-25 and 25-75 mm) and live (0-6, 6-25 mm) fuels, collecting percent cover and depth/height (cm) of the various fuel components, and classifying observations into 19 fuelbed categories. To ensure comparability with existing vegetation classification systems, we classified each observation according to the European Fuel Map, the Corine Land Cover classes (level IV), the European Forest Types, and the forest categories of the Italian National Forest Inventory. The dataset and a photo description of each fuelbed category are available as Supplementary material. This dataset is the first step to develop several products at the national scale such as: (i) fuel type classification and mapping; (ii) carbon stock and wildfire emission estimates; (iii) calibration of fuel models for the simulation of fire behavior and effects. [ABSTRACT FROM AUTHOR]

Coppice silviculture has a long tradition in Italy. Societal demands have led to the development of forest management techniques for integrating wood production with other kinds of forest uses and regulations have been issued to limit forest degradation. In Italy, 35% of the national forest cover is currently managed under coppice silvicultural systems that provide 66% of the annual wood production. Fuel-wood demand is increasing and a large amount of fuelwood is currently imported in Italy. Modern coppice practices differ from those adopted in the past and may have a reduced impact on ecosystem characteristics and processes. Nevertheless, coppice silviculture has a bad reputation mostly on grounds that are beyond economic, technical and ecological rationales. Neither cessation of use nor a generalized conversion from coppice to high forest are likely to respond simultaneously to the many demands deriving from complex and articulated political and economic perspectives operating at global, European, national, regional and forest stand-level scales. Different approaches of modern silviculture to coppice successfully tested in Italy for more than a decade are illustrated. We propose to combine different options at the stand and sub-stand level, including either development without human interference or conversion to high forest, and to apply these approaches within the framework of novel forest management plans and regionally consistent administrative procedures. This bottom-up approach represents a potential solution to the socio-economic and environmental challenges affecting coppicing as a silvicultural system. [ABSTRACT FROM AUTHOR]

Crop damages by wildlife is a frequent form of human-wildlife conflict. Identifying areas where the risk of crop damages is highest is pivotal to set up preventive measures and reduce conflict. Species distribution models are routinely used to predict species distribution in response of environmental changes. The aim of this paper was assessing whether species distribution models can allow to identify the areas most at risk of crop damages, helping to set up management strategies aimed at the mitigation of human-wildlife conflicts. We obtained data on wild boar Sus scrofa damages to crops in the Alta Murgia National Park, Southern Italy, and related them to landscape features, to identify areas where the risk of wild boar damages is highest. We used MaxEnt to build species distribution models. We identified the spatial scale at which landscape mostly affects the distribution damages, and optimized the regularization parameter of models, through an information-theoretic approach based on AIC. Wild boar damages quickly increased in the period 2007-2011; cereals and legumes were the crops more affected. Large areas of the park have a high risk of wild boar damages. The risk of damages was related to low cover of urban areas or olive grows, intermediate values of forest cover, and high values of shrubland cover within a 2-km radius. Temporally independent validation data demonstrated that models can successfully predict damages in the future. Species distribution models can accurately identify the areas most at risk of wildlife damages, as models calibrated on data collected during only a subset of years correctly predicted damages in the subsequent year. [ABSTRACT FROM AUTHOR]