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Background: Throughout their range, red deer are a well-studied species. In Italy, this species occupies two ecologically different ranges: the Alps and the Apennines. Although several studies have described the spatial behaviour of red deer in the Italian Alps, no data are available for the Apennine population. Results: The spatial behaviours of 13 deer from the Northern Apennines range were analysed for the first time using GPS-GSM telemetry from 2011 to 2017. Red deer displayed two coexisting strategies, i.e., migratory and stationary. In our sample, females tended to migrate more than males. We found a high level of interindividual variability in the date of migration/return, while each migratory deer was very conservative during the study period. The migration ranges were on average 12 ± 4.2 km from the resident range. Both migratory and resident deer displayed high site fidelity. No switch from the migratory to stationary strategy was observed for any deer during the study period; however, the period could have been too short to detect any switch. At the management level, over 18 management cycles occurred during the study period, and a spatial mismatch was found between deer range and management units (districts) in 38.9% (7) of the cases. Merging the districts belonging to each province to obtain an area of approximately 1000 km2 would partially address such spatial mismatch, reducing its occurrence to 22%. Conclusions: Despite the small sample size, these results can guide future management actions. However, an in-depth study with a larger sample size is required to better understand and manage the red deer Apennines population. [ABSTRACT FROM AUTHOR]

The use of a Remotely Piloted Aircraft System (RPAS) for the characterization and monitoring of landslides has been widely improved in the last decade. In particular, the use of this system is particularly effective for the study of areas prone to geohazards. Zones affected by landslides, such as rock slides and debris flows, are often quite critical in terms of accessibility due to unstable blocs that can strongly limit the direct access to the studied area. In this paper, we present the case study of Ponte Formazza in NW Italian Alps. In June 2019, a massive and complex debris flow re-mobilized about 300,000 m3 of a rockslide deposit that occurred in 2009. In this particular environment, we tested traditional, direct and mixed photogrammetric approaches using various configurations of Ground Control Points (GCPs) of the photogrammetric block and by calculating the relative errors. The minimum configuration of GCPs was established to reduce in situ measurements without degrading the accuracy of the cartographic products. The images of three RPAS campaigns (2017, 2018 and 2019), processed with a Structure from Motion (SfM) technique, allowed us to obtain very high-resolution orthophoto and digital surface models (DSMs) before and after the 2019 event. A few GCPs, geolocated with a Global Navigation Satellite System (GNSS), improved the orthophoto and DSM quality (Root Mean Squared Error RMSE 5 cm) even in the areas far from the drone deployment. The availability of high-resolution models has been fundamental for the identification of the volume changes. Furthermore, the 3D view supported and completed the geomorphological mapping of affected areas, particularly in the areas where the field survey is dangerous. The use of ancillary meteorological data and Sentinel-2 satellite images allows for a better definition of the kinematics and the predisposal and triggering factors of the 2019 debris flow. [ABSTRACT FROM AUTHOR]

Abstract: Monitoring constitutes a key element in the management and conservation of many mammal species. We describe a technique to obtain population indices for red squirrels (Sciurus vulgaris) using hair-tubes and compare these indices to population estimates obtained by live trapping. Data were collected in seven study areas in the Western and Central Alps in Italy and compared with data previously collected in 11 sites in northern England. The aim was to test if hair-tube census could be used to derive a general predictive model allowing accurate predictions of squirrel numbers in different years, habitats and geographic regions. We used model equations developed from the proportion of hair-tubes visited to predict densities obtained from live-trapping. Hair-tube data gathered in the Central Alps correctly predicted squirrel densities in the Western Alps. A combined data set pooling the sites of these two regions based on the first three years successfully predicted the two successive years. In addition, a combined model derived from areas monitored for five years had a high predictive value locally (89%) and internationally (73%) when applied to the English data set. We therefore believe that the predictive model developed in this study could be of general value and be used to monitor squirrel populations in European low density conifer habitats (0.1–0.5 squirrels/ha). The approach may also be suitable for many tree squirrel populations in North America and other arboreal rodents that occur at similar densities. [Copyright &y& Elsevier]