Search Results (2)

African swine fever (ASF) is a highly contagious viral disease with significant impacts on domestic pigs and wild boar populations. This study applies GIS-based spatial analysis to monitor ASF outbreaks in northwestern Italy (Piedmont and Liguria) and identify areas at increased risk. Key factors considered include pig density, wildlife proximity, and environmental conditions. The spatial analysis revealed that central–western municipalities exhibited higher risk due to favorable environmental conditions and dense wild boar populations, while peripheral areas showed a temporal delay in outbreak emergence. Mapping the spreading rate and habitat interfaces allowed the development of a spatial risk model, which was further analyzed using geostatistical techniques to understand disease dynamics. The results demonstrate the effectiveness of geospatial modeling in identifying high-risk zones, characterizing spatio-temporal patterns, and supporting targeted prevention and surveillance strategies. These findings provide actionable insights for ASF management and resource allocation. Future studies may refine these models by integrating additional datasets and environmental variables, enhancing predictive capacity and applicability across different regions. Full article

This research focuses on the recent pollen image of several vegetation types in NW Italy. In 201 arboreal, shrubby, and herbaceous plant populations, pollen samples were taken from moss polsters, and the corresponding vegetation was recorded using the phytosociological method. Since studies on recent pollen rain in the Mediterranean mountains and coast are rare, this research aims to provide new data and tools to better interpret fossil pollen spectra. Pollen analysis provided data for the comparison between surface spectra and vegetation. Davis indices, fidelity, dispersion, and the relation with vegetation data were calculated for each taxon, and PCA was carried out. Most vegetation types are identifiable through the taxa dominating the pollen spectra, as frequently happens in woodlands (e.g., beech woods, chestnut woods, etc.). Characterizing shrubland and certain tree-dominated vegetation types (e.g., Larix forests) through pollen data is more complex. In this regard, Davis indices are particularly useful for identifying pollen/plant association, over- and underrepresentation of pollen, and taxa indicating vegetation types. Pollen threshold values were calculated which allow the assessment of the local presence of a plant. Overall, the achieved results partially confirm those of previous research carried out in the region, greatly expanding the comparisons between several different plant communities and the database in view of future sharing through the EMPD. Full article