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A critical challenge for urban forests is the arrival of Toumeyella parvicornis (or pine tortoise scale) in Italy, as this species damages stone pine (Pinus pinea L.), an emblematic Mediterranean species. The aim of this study is to evaluate the effectiveness of remote-sensing data for monitoring pest invasions in the urban area of Rome, using PlanetScope images with a 1-day revisit time and 3 m spatial resolution, making them ideal for detecting outbreaks in complex urban areas. First, we constructed a reference dataset, georeferencing 238 healthy trees in Tenuta San Rossore (Tuscany) and more than 2000 damaged trees in Rome's green areas. In any case, this dataset of healthy trees—obtained from forest areas—was expected to exhibit higher photosynthetic activity compared to urban green areas. Second, more than 30,000 PlanetScope images were analyzed to test the effectiveness of the Renormalized Difference Vegetation Index in detecting this specific forest disturbance. Finally, different thresholds were examined, allowing for the identification of an optimal threshold to discriminate healthy trees from damaged trees. The index results showed a marked drop during the summer in the infested areas, compared to the healthy areas. The identified threshold provided 99% accuracy in detecting infested trees. The approach applied in this study demonstrated that PlanetScope imagery proved effective in detecting T. parvicornis, leading to promising results. [ABSTRACT FROM AUTHOR]

This study aims to present a methodological approach based on the objectives of the Nature Restoration Law and the concept of Forest Landscape Restoration to identify areas that are best suited for the implementation of Nature-based Solutions for the improvement of landscape and habitat status in the city of Campobasso (1028.64 km2). Using open data (ISPRA ecosystem services and regional land use capability), an expert based approach (questionnaire), and a multicriteria analysis (Analytical Hierarchy Process), the Total Ecosystem Services Value index was determined as a weighted additive sum of the criteria considered. The index was then classified into eight clusters, and the land use "Cropland" was extracted. Cluster 1 croplands (740.09 Ha) were identified as the areas to be allocated to Nature-based Solutions since they were those characterized by fewer ecosystem services provisioning, while Cluster 8 croplands (482.88 Ha) were identified as valuable areas to be preserved. It was then possible to compare the "Forest" areas currently present in the study area with those of a possible future scenario, represented by the areas occupied today by forest with the addition of Cluster 1 croplands. A landscape analysis was conducted; it showed greater dispersion and fragmentation of forest patches in the future scenario, but also greater connectivity and thus greater ecological functionality of the patches. [ABSTRACT FROM AUTHOR]

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]

Forests cover nearly 40% of European land, with different country percentage and patchy distribution. The European forestry sector highlights that forest areas have different ownership: private (by firms, individual, or organizations) and public (State, communities or municipalities). The number of forestry holdings, size of landholding, and ownership types influence and drive forest management, governance and various other socio-economic linked issues. Moreover, forest owners determine management objectives and policies which influence the application of Sustainable Forest Management (SFM) practices. Several tools were developed to promote SFM, including forest certification. Numerous forest certification schemes are present across the world but the Forest Stewardship Council (FSC) and the Programme for the Endorsement of Forest Certification (PEFC) are those prevalent. However, a map of certified forests is lacking, although mapping would be essential to locate the percentage of forest that are certified to be sustainably managed. The study mapped forest certification across 43 European states, according to 499 FSC and 284 PEFC reports and assessed the proportion of certified forest area on public and private land and the rate of increase. This research was carried out collecting information on European certified forest companies/owners and locating geographically their forests at sub-national level (regions, NUTS 2). The database of the Joint COST Action FACESMAP/UNECE/FAO was an important data source. At European level, about six percent of the forest is certified under FSC scheme, while about seven percent under PEFC scheme. As forest certification is a useful tool to manage forests aiming at the integration of economic, ecological and social sustainability, the knowledge of the location and area of certified forest in Europe could be important in motivating decision makers to increase these sustainably managed areas. [ABSTRACT FROM AUTHOR]

Forest fires, together with the decline of silviculture practice, are one of the most important natural disturbances affecting Mediterranean forests. The year 2017 is shaping up to be a record breaking fire season all around Southern Europe and especially in Italy for the sheer amount of hectares burned. Here we discuss about the importance of forest fire management, highlighting the role of prescribed burning and mechanical treatment (e.g., manual removal, thinning) in reducing the risk of high-intensity wildfires. We report on the successful applications of those fire management techniques on the pinewoods of Vesuvio National Park and Castel Fusano Natural Reserve. The information compiled in the present article aims to demonstrate the potential relevance and impact of forest resources management for fire hazard reduction and shows the necessity of strong interaction among not only the scientific community, but also forest managers, decision makers and the civic responsibility of society at large. [ABSTRACT FROM AUTHOR]

We present an innovative method based on the application of inverse yield models for producing spatially explicit estimations of forest age. Firstly, a raster growing stock volume map was produced using the non-parametric k- Nearest Neighbors estimation method on the basis of IRS LISS-III remotely sensed imagery and field data collected in the framework of a local forest inventory. Secondly, species-specific inverted yield equations were applied to estimate forest age as a function of growing stock volume. The method was tested in 128 000 ha of even-aged forests in central Italy (Molise region). The accuracy of the method was assessed using an independent dataset of 305 units from a local standwise forest inventory. The results demonstrated that the forest age map was accurate, with a root mean square error of 15.8 years (30% of the mean of field values), and useful for supporting forest management purposes, such as the assessment of harvesting potential and ecosystem services. Thanks to the use of remotely sensed data and spatial modeling, the proposed approach is cost-effective and easily replicable for vast regions. [ABSTRACT FROM AUTHOR]