Search Results (76)

Beech forests in the Italian peninsula are actively managed and they also support a high level of biodiversity. Hence, biodiversity conservation can be synergistic with timber production and carbon sequestration, enhancing the overall economic benefits of forest management. This study aimed to evaluate the effect of forest management regimes on bird communities in the Italian Peninsula during 2022 through audio recordings. We studied the structure, composition, and specialization of the breeding bird community in four managed beech stands (three even-aged beech stands aged 20, 60, and 100 years old, managed by a uniform shelterwood system; one uneven-aged stand, managed by a single-tree selection system) and one uneven-aged, unmanaged beech stand in the northern Apennines (Tuscany region, Italy). Between April and June 2022, data were collected through four 1-hour audio recording sessions per site, analyzing 5 min sequences. The unmanaged stand hosted a richer (a higher number of species, p < 0.001) and more specialized (a higher number of cavity-nesting species, p < 0.001; higher Woodland Bird Community Index (WBCI) values, p < 0.001; and eight characteristic species, including at least four highly specialized ones) bird community, compared to all the managed forests; moreover, the latter were homogeneous (similar to each other). Our study suggests that the unmanaged beech forests should be a priority option for conservation, while in terms of the managed beech forests, greater attention should be paid to defining the thresholds for snags, deadwood, and large trees to be retained to enhance their biodiversity value. Studies in additional sites, conducted over more years and including multi-taxon communities, are recommended for a deeper understanding and generalizable results. Full article

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article

The NW–SE-trending Firenze-Pistoia Basin (FPB) is an intermontane tectonic depression in the Northern Apennines (Italy) bounded to the northeast by a SW-dipping normal fault system. Although it has moderate historical seismicity (maximum estimated Mw 5.5 in 1895), the FPB lacks detailed characterization of its recent tectonic structures, unlike those of nearby basins that have produced Mw > 6 events. This study focuses on the southeastern sector of the basin, including the urban area of Florence, using tectonic geomorphology derived from remote sensing, in particular LiDAR data, field verification, and high-resolution geophysical surveys such as electrical resistivity tomography and seismic reflection profiles. The integration of these techniques enabled interpretation of the subdued and anthropogenically masked tectonic structures, allowing the identification of Holocene activity and significant, although limited, surface vertical offset for three NE–SW-striking normal faults, the Peretola, Scandicci, and Maiano faults. The Scandicci and Maiano faults appear to segment the southeasternmost strand of the master fault of the FPB, the Fiesole Fault, which now shows activity only along isolated segments and cannot be considered a continuous active fault. From empirical relationships, the Scandicci Fault, the most relevant among the three active faults, ~9 km long within the basin and with an approximate Late Quaternary slip rate of ~0.2 mm/year, might source Mw > 5.5 earthquakes. These findings highlight the need to reassess the local seismic hazard for more informed urban planning and for better preservation of the cultural and architectural heritage of Florence and the other artistic towns located in the FPB. Full article

This study presents a comprehensive methodology for the detection and characterization of fractures in geological samples using X-ray computed tomography (CT). By combining convolution-based image processing techniques with advanced neural network-based segmentation, the proposed approach achieves high precision in identifying complex fracture networks. The method was applied to a marly limestone sample from the Maiolica Formation, part of the Umbria–Marche stratigraphic succession (Northern Apennines, Italy), a geological context where fractures often vary in size and contrast and are frequently filled with minerals such as calcite or clays, making their detection challenging. A critical part of the work involved addressing multiple sources of uncertainty that can impact fracture identification and measurement. These included the inherent spatial resolution limit of the CT system (voxel size of 70.69 μm), low contrast between fractures and the surrounding matrix, artifacts introduced by the tomographic reconstruction process (specifically the Radon transform), and noise from both the imaging system and environmental factors. To mitigate these challenges, we employed a series of preprocessing steps such as Gaussian and median filtering to enhance image quality and reduce noise, scanning from multiple angles to improve data redundancy, and intensity normalization to compensate for shading artifacts. The neural network segmentation demonstrated superior capability in distinguishing fractures filled with various materials from the host rock, overcoming the limitations observed in traditional convolution-based methods. Overall, this integrated workflow significantly improves the reliability and accuracy of fracture quantification in CT data, providing a robust and reproducible framework for the analysis of discontinuities in heterogeneous and complex geological materials. Full article

Sedimentary basins developed in mountain belts are natural traps of catchment erosion products and can produce comprehensive palaeoflood records that extend beyond instrumental or historical data. This study investigates the Lake Moo plain (1120 m a.s.l.), located in the Mt. Ragola (1712 m a.s.l.) ophiolitic massif in the Northern Apennines (Italy), which serves as an excellent case study for inferring the chronology of past flood events due to its position relative to the dominant atmospheric flow and its favorable geological and geomorphological characteristics. The Northern Apennines is a relatively understudied region regarding the reconstruction of past Holocene flood activity through the analysis of lake sediments and peat bogs, compared with areas like the Alps. The main objective of this research was to analyze sediment cores taken from a lake situated in a catchment area dominated by ultramafic rock lithologies and associated residual weathering cover deposits. This allowed us to detect and characterize past flood events in the Ligurian–Emilian Apennines. A multidisciplinary approach, integrated with reference data on geology, geomorphology, pedology, and petrography, enabled a more detailed description of the changes in the hydrologic cycle. Collectively, these data suggest that periods of increased past flood activity were closely linked to phases of rapid climate change at the scale of the Ligurian–Emilian Apennines. The preliminary results suggest that floods occurring during periods of temperature drops have distinct characteristics compared with those during temperature rises. Full article

This work presents the use of remote sensing data for land cover mapping with a case of Central Apennines, Italy. The data include 8 Landsat 8-9 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) satellite images in six-year period (2018–2024). The operational workflow included satellite image processing which were classified into raster maps with automatically detected 10 classes of land cover types over the tested study. The approach was implemented by using a set of modules in Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS). To classify remote sensing (RS) data, two types of approaches were carried out. The first is unsupervised classification based on the MaxLike approach and clustering which extracted Digital Numbers (DN) of landscape feature based on the spectral reflectance of signals, and the second is supervised classification performed using several methods of Machine Learning (ML), technically realised in GRASS GIS scripting software. The latter included four ML algorithms embedded from the Python’s Scikit-Learn library. These classifiers have been implemented to detect subtle changes in land cover types as derived from the satellite images showing different vegetation conditions in spring and autumn periods in central Apennines, northern Italy. Full article

The sonoscape of a small town at the foot of the Northern Apennines Mountains in north–central Italy was studied using a regular grid of automatic recording devices, which collected ambient sounds during the spring of 2024. The study area is characterized by high landscape heterogeneity, a result of widespread suburban agricultural abandonment and urban development. Sonic data were analyzed using the Sonic Heterogeneity Index and nine derivative metrics. The sonic signatures from 26 stations exhibited distinct, spatially explicit patterns that were hypothesized to be related to a set of 11 landcover types and seven landscape metrics. The unique sound profile of each sample site was consistent with the emerging heterogeneity of landcover typical of many Mediterranean regions. Some sonic indices exhibited stronger correlations with landscape metrics than others. In particular, the Effective Number of Frequency Bins Ratio (ENFBr) and Sheldon’s Evenness (E) proved particularly effective at revealing the link between sonic processes and landscape patterns. The sonoscape and landscape displayed correlations significantly aligned with their variability, highlighting the ecological heterogeneity of the sonic and physical domains in the study area. This case study underscores the importance of selecting appropriate metrics to describe complex ecological processes, such as the relationships and cause-and-effect dynamics of environmental sounds among human altered landscapes. Full article

Forest Orchidaceae are important for European temperate forests, yet their distribution and abundance have so far interested limited research. In three pure or mixed silver fir stands in the Foreste Casentinesi National Park (NP) (Northern Apennines, Italy) we analysed how structural traits in mature and old-growth forests affected orchid communities in terms of abundance of the main genera, trophic strategy and rarity in the NP. We established three 20 × 60 m plots to quantify the structure of living and dead tree community, including a set of old-growth attributes connected to large trees, deadwood, and established regeneration. In each plot, we measured the abundance of all orchid species and explored their behaviour according to the trophic strategy (autotrophy/mixotrophy, obligate mycoheterotrophy), rarity within the NP, and threatened status according to the IUCN Red List. We used multivariate ordination and classification techniques to assess plot similarities according to forest structure and Orchid Community and identify the main structural factors related to orchid features. The main structural factors were used as predictors of community traits. Forest composition (i.e., the dominance/abundance of silver fir) affected the presence of the main orchid genera: Epipactis were abundant in silver fir-dominated forests, Cephalanthera in mixed beech and fir forests. Interestingly, Cephalanthera could become limited even in beech-dominated conditions if fir regeneration was abundant and established. Old-growth attributes like the density of deadwood and large tree volume were important determinants of the presence of rare and mycoheterotrophic species. Our results provided a first quantitative description of forest reference conditions to be used in the protection and restoration of threatened and rare orchid species. Full article

The bush cricket Saga pedo, listed as Vulnerable globally by the IUCN and included in Annex IV of the EU Habitats Directive, is a parthenogenetic species highly sensitive to environmental changes, facing threats from forest expansion and agricultural intensification. S. pedo prefers dry, open habitats with sparse vegetation, and its pronounced thermo-heliophily makes it an indicator of xerothermic habitats. In many areas of Italy, including the Northern Apennines (Piedmont), semi-natural grasslands are fragmented. Open habitats have been reduced to small, isolated patches surrounded by forests due to the abandonment of agropastoral activities. Consequently, the occurrence of open habitat species is related to the quality and availability of suitable areas and ecological connectivity. We developed a spatial Bayesian framework to identify areas of occurrence for S. pedo. Using the inverse probability of occurrence, we derived ecological corridors among suitable patches. Our findings indicate that the occurrence and connectivity of S. pedo are reduced by intensive cultivation but favored by open habitats with 10–50% woody tree cover, suggesting sustainable land management is crucial for supporting the species. Given the extinction risk S. pedo faces, we urge local administrations to maintain and improve suitable areas and guarantee the network of ecological corridors identified. Full article

Rough surfaces known as stylolites are common geological features that are developed by pressure solution, especially in carbonate rocks, where they are used as strain markers and as stress gauges. As applications are developing in various geological settings, questions arise regarding the uncertainties associated with quantitative estimates of paleostress using stylolite roughness. This contribution reports for the first time a measurement of the temperature at which pressure solution was active by applying clumped isotopes thermometry to calcite cement found in jogs linking the tips of the stylolites. This authigenic calcite formed as a redistribution of the surrounding dissolved material by the same dissolution processes that formed the extensive stylolite network. We compare the depth derived from these temperatures to the depth calculated from the vertical stress inversion of a bedding parallel stylolite population documented on a slab of the Calcare Massiccio formation (early Jurassic) formerly collected in the Umbria-Marches Arcuate Ridge (Northern Apennines, Italy). We further validate the coevality between the jog development and the pressure solution by simulating the stress field around the stylolite tip. Calcite clumped isotopes constrain crystallization to temperatures between 35 and 40 °C from a common fluid with a δ¹⁸O signature around −1.3‰ SMOW. Additional δ¹⁸O isotopes on numerous jogs allows the range of precipitation temperature to be extended to from 25 to 53 °C, corresponding to a depth range of 650 to 1900 m. This may be directly compared to the results of stylolite roughness inversion for stress, which predict a range of vertical stress from 14 to 46 MPa, corresponding to depths from 400 to 2000 m. The overall correlation between these two independent depth estimates suggests that sedimentary stylolites can reliably be used as a depth gauge, independently of the thermal gradient. Beyond the method validation, our study also reveals some mechanisms of pressure solution and the associated p,T conditions favouring their development in carbonates. Full article

In mountain environments, landslide activity can be assessed through a combination of remote and proximal sensing techniques performed at different scales. The complementarity of methods and the synergistic use of data can be crucial for landslide recognition and monitoring. This paper explored the potential of Multi-Temporal Differential Synthetic Aperture Radar Interferometry (MT-DInSAR) to detect and monitor slope deformations at the basin scale in a catchment area of the Northern Apennines (Italy) and verified the consistency between the landslide classification by the Inventory of Landslide Phenomena in Italy (IFFI) and displacements from the SAR data. In this research, C- and X-band SAR were considered to provide insights into the performances and suitability of sensors operating at different frequencies. This study provides clues about the state of activity of slow-moving landslides and critically assessed its contribution to the IFFI inventory update. Moreover, it demonstrated the benefits of the synergistic use of SAR and geomorphological analysis to investigate slope dynamics in clayey terrains by exemplifying the approach for a relevant case study, the Gaiato landslide. Notwithstanding the widespread use of MT-DInSAR for landslide kinematics investigations, the main limiting factors are discussed along with the expected improvements related to the upcoming new generations of L-band SAR satellites. Full article

Increasing water withdrawals and changes in land cover/use are critically altering surface water bodies, often causing a noticeable reduction in their area. Such anthropogenic modification of surface waters needs to be thoroughly examined to recognize the dynamics through which humans affect the loss of surface water. By leveraging remotely-sensed data and employing a distance–decay model, we investigate the loss of surface water resources that occurred in Italy between 1984 and 2021 and explore its association with land cover change and potential human pressure. In particular, we first estimate the land cover conversion across locations experiencing surface water loss. Next, we identify and analytically model the influence of irrigated and built-up areas, which heavily rely on surface waters, on the spatial distribution of surface water losses across river basin districts and river basins in Italy. Our results reveal that surface water losses are mainly located in northern Italy, where they have been primarily replaced by cropland and vegetation. As expected, we find that surface water losses tend to be more concentrated in the proximity of both irrigated and built-up areas yet showing differences in their spatial occurrence and extent. These observed spatial patterns are well captured by our analytical model, which outlines the predominant role of irrigated areas, mainly across northern Italy and Sicily, and more dominant effects of built-up areas across the Apennines and in Sardinia. By highlighting land cover patterns following the loss of surface water and evaluating the relative distribution of surface water losses with respect to areas of human pressure, our analysis provides key information that could support water management and prevent future conditions of water scarcity due to unsustainable water exploitation. Full article

The combined use of Uncrewed Aerial Vehicles (UAVs) with an integrated Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS) module and an external GNSS base station allows photogrammetric surveys with centimeter accuracy to be obtained without the use of ground control points. This greatly reduces acquisition and processing time, making it possible to perform rapid monitoring of landslides by installing permanent and clearly recognizable optical targets on the ground. In this contribution, we show the results obtained in the Ca’ Lita landslide (Northern Apennines, Italy) by performing multi-temporal RTK-aided UAV surveys. The landslide is a large-scale roto-translational rockslide evolving downslope into an earthslide–earthflow. The test area extends 60 × 10³ m² in the upper track zone, which has recently experienced two major reactivations in May 2022 and March 2023. A catastrophic event took place in May 2023, but it goes beyond the purpose of the present study. A total of eight UAV surveys were carried out from October 2020 to March 2023. A total of eight targets were installed transversally to the movement direction. The results, in the active portion of the landslide, show that between October 2020 and March 2023, the planimetric displacement of targets ranged from 0.09 m (in the lateral zone) to 71.61 m (in the central zone). The vertical displacement values ranged from −2.05 to 5.94 m, respectively. The estimated positioning errors are 0.01 (planimetric) and 0.03 m (vertical). The validation, performed by using data from a permanent GNSS receiver, shows maximum differences of 0.18 m (planimetric) and 0.21 m (vertical). These results, together with the rapidity of image acquisition and data processing, highlight the advantages of using this rapid method to follow the evolution of relatively rapid landslides such as the Ca’ Lita landslide. Full article

Variations in the CO₂ dissolved in water springs have long been observed near the epicenters of moderate and strong earthquakes. In a recent work focused on data collected during the 2017–2021 period from a monitoring site in the Northern Apennines, Italy, we noticed a significant correlation between CO₂ anomalies and moderate-to-weak seismic activity. Here, we extended this analysis by focusing on data collected from the same site during a different period (2010–2013) and by integrating the CENSUS method with an artificial neural network (ANN) in the already-tested protocol. As in our previous work, a fit of the computed residual CO₂ distributions allowed us to evidence statistically relevant CO₂ anomalies. Thus, we extended a test of the linear dependence of these anomalies to seismic events over a longer period by means of binary correlations. This new analysis also included strong seismic events. Depending on the method applied, we observed different time lags. Specifically, using the CENSUS methodology, we detected a CO₂ anomaly one day ahead of the earthquake and another anomaly eleven days ahead. However, no anomaly was observed with the ANN methodology. We also investigated possible correlations between CO₂ concentrations and rain events and between rain events and earthquakes, highlighting the occurrence of a CO₂ anomaly one day after a rain event of at least 10 mm and no linear dependence of seismic and rain events. Similar to our previous work, we achieved a probability gain of around 4, which is the probably of earthquake increases after CO₂ anomaly observations. Full article

Onopordum tauricum Willd., a species distributed in Eastern Europe, has been the subject of various research endeavors aimed at assessing its suitability for extracting vegetable rennet for use in the production of local cheeses as a substitute for animal-derived rennet. In Italy, the species has an extremely fragmented and localized distribution in six locations scattered across the central-northern Apennines and some areas of southern Italy. In this study, both the morphology and genetic diversity of the six known Italian populations were investigated to detect putative ecotypes. To this end, 33 morphological traits were considered for morphometric measurements, while genetic analysis was conducted on the entire genome using the ddRAD-Seq method. Both analyses revealed significant differences among the Apennine populations (SOL, COL, and VIS) and those from southern Italy (ROT, PES, and LEC). Specifically, the southern Italian populations appear to deviate significantly in some characteristics from the typical form of the species. Therefore, its attribution to O. tauricum is currently uncertain, and further genetic and morphological analyses are underway to ascertain its systematic placement within the genus Onopordum. Full article