Climate change and global food demand in coming decades urge effective actions for more efficient uses of water and soil resources. This paper reports the preliminary findings of a study assessing the potential of sheep scoured wool residues (SWRs) as soil amendments to enhance the physical and hydraulic properties of a sandy loam soil under rain conditions.

Ink disease, primarily caused by the pathogen Phytophthora xcambivora, significantly threatens the health and productivity of sweet chestnut (Castanea sativa Mill.) orchards, highlighting the need for accurate detection methods. This study investigates the efficacy of machine learning (ML) classifiers combined with high-resolution multispectral imagery acquired via unmanned aerial vehicles (UAVs) to assess chestnut tree health at a site in Tuscany, Italy. Three machine learning algorithms—support vector machines (SVMs), Gaussian Naive Bayes (GNB), and logistic regression (Log)—were evaluated against eight vegetation indices (VIs), including NDVI, GnDVI, and RdNDVI, to classify chestnut tree crowns as either symptomatic or asymptomatic. High-resolution multispectral images were processed to derive vegetation indices that effectively captured subtle spectral variations indicative of disease presence. Ground-truthing involved visual tree health assessments performed by expert forest pathologists, subsequently validated through leaf area index (LAI) measurements. Correlation analysis confirmed significant associations between LAI and most VIs, supporting LAI as a robust physiological metric for validating visual health assessments. GnDVI and RdNDVI combined with SVM and GNB classifiers achieved the highest classification accuracy (95.2%), demonstrating their superior sensitivity in discriminating symptomatic from asymptomatic trees. Indices such as MCARI and SAVI showed limited discriminative power, underscoring the importance of selecting appropriate VIs that are tailored to specific disease symptoms. This study highlights the potential of integrating UAV-derived multispectral imagery and machine learning techniques, validated by LAI, as an effective approach for the detection of ink disease, enabling precision forestry practices and informed orchard management strategies.

Ecosystem engineers such as beavers play a key role in shaping their habitats by modifying their physical environment and providing resources for other species. Beavers alter their surroundings by building dams, lodges, and canals, ultimately transforming rivers into dynamic networks of ponds and wetlands that may enhance biodiversity, by benefiting both terrestrial and aquatic wildlife. Rivers and the surrounding vegetation cover such as gallery and riparian forests are key habitats to several taxa, including bats and small mammals, two species-rich and conservation-relevant groups of vertebrates. Riverine ecosystems provide foraging, shelter, and commuting opportunities to these mammals. Recent evidence from northern Europe and North America suggests positive impacts on bat populations by beaver activities, due to the increased abundance of aquatic insects in beaver-modified environments, whereas the effects upon small mammals are less known. We aimed at assessing the effects of recently released beavers upon conservation relevant bats and small mammals in a Mediterranean context by following a bioacoustics monitoring approach. We compared bat and hazel dormouse diversity and activity at sites with and without beaver activity along three rivers in central Italy. Acoustic surveys confirmed higher bat and hazel dormouse activity levels at “beaver” sites with respect to control ones, particularly in areas surrounded by higher forest cover. Beaver sites exhibited a more pronounced positive response in bat activity levels as the surrounding forest cover increased. We also report that acoustically-detected hazel dormouse responded positively to beaver presence. We thus showed that both bats and dormice appeared to benefit from the presence of beavers at the sampled sites. Our study sheds light the ecological importance of beavers in enhancing habitat diversity and promoting biodiversity across aquatic and terrestrial ecosystems, highlighting positive effects upon conservation relevant taxa.

DIGITgame, intends to improve scientific skills and competences through an innovative teaching methods. It is based on Smart City projecting and realized by the development of a mini-game with challenges based on the scientific concepts. DIGITgame proposes a new approach to teach traditional topics of environmental sciences using the thematic of Smart Cities and taking advantage introducing the videogame solution. It will permit to reinforce the achievement of advanced and high quality competences, both in scientific topics and digital knowledge. Match between traditional teaching approach, gamification challenge and informatics is the keystone to turn students in involved and aware citizens.