Bottom trawling affects seabed habitats, but its large-scale impacts remain poorly quantified. Assessment of trawling impacts is essential to support monitoring and achieving sustainability objectives under international conventions, sustainable development goals, and seafood certification programs. We present a Europe-wide quantitative assessment of bottom trawling impacts, accounting for regional seabed-community sensitivity drivers, across the Baltic, Atlantic, Mediterranean and Black Sea continental shelves. Using two risk-based indicators of seabed status-Relative Benthic Status determined as benthic community biomass relative to seabed fauna carrying capacity (RBStot) and RBSsen (biomass of the 10% most sensitive fauna relative to carrying capacity)-we found substantial regional and habitat differences. The Black, Baltic and Aegean-Levantine Seas showed low trawling intensity and high seabed status across habitats. In contrast, the Western Mediterranean, Ionian and Central Mediterranean and Adriatic Seas were the most severely impacted. Trawling affected the sensitive species biomass fraction more strongly than the total community biomass. RBStot was in good condition (here chosen as RBS > 75% for epifauna) for over 79% of habitat-ecoregion combinations. In contrast, RBSsen met this threshold in only 46% of these. A strong correlation emerged between the mean trawling intensity and RBStot and RBSsen, allowing the use of SAR to estimate ecosystem status. This relationship can support decisions on where, and by how much, SAR reductions are needed to achieve good environmental status in regions where no detailed assessment is available. Our approach provides a quantitative framework to balance fishery production with ecosystem sustainability, offering tools for environmental and fisheries management in Europe.
Soil biodiversity remains one of the least systematically studied components of global biodiversity, largely invisible in policy agendas. A coordinated soil biodiversity monitoring approach is urgently needed to enable national‐level action.
Geological mapping provides the basic knowledge for understanding the eruptive and temporal evolution of a volcanic area. Because of their increasing availability and resolution, Digital Terrain Models (DTMs) are extensively and fruitfully used in volcanology as an additional tool for recognizing and classifying geomorphological features and assisting field survey and mapping tasks. This study focuses on the application of Red Relied Image Maps (RRIMs), derived from a high-resolution 1 m pixel/resolution DTM and complemented and validated with fieldwork, to identify and outline partially hidden volcanic features at an intensely vegetated volcano. We present here the results of the application of this method at Monte Amiata volcano (southern Tuscany, Italy), an effusive, silicic Middle Pleistocene volcano with a massive hardwood forest cover, whereas we identified elongated and plateau-like lava flows at the base of the volcano and coulees and overlapped rounded domes at the top. In addition, we performed a localized Fourier transform (i.e., S-Transform spectral analysis) for determining the dominant frequencies and identifying repeating patterns of the largest lava flows to quantify their surface folding pattern. These analyses were based on differential openness and RRIMs data at different scales (1, 10, and 100 m) and DTMs resolutions (1 and 10 m). We demonstrate that the extensive use of these mapping tools can represent an effective method for recognizing and interpreting otherwise hidden volcanic structures. We suggest that applying DTM-derived parameters should be considered a necessary step for the precise mapping of remote or heavily vegetated volcanic areas.
Human impacts on species and ecosystems are increasing at a drastic rate. Raptors, a group of birds particularly vulnerable due to their ecological traits, are heavily affected by a variety of direct and indirect threats. Identifying important areas used during the breeding season and assessing exposure to main risks is crucial for promoting effective management and conservation strategies. We GPS-tracked 25 Eleonora's Falcons Falco eleonorae, i.e. 2% of the Italian breeding population from a colony in Sardinia, and identified an Important Conservation Area (ICA) of 8,099 km2. This ICA spans Sardinia (Italy, 83%) and Corsica (France, 17%), with only 29.1% of its area covered by Natura 2000 sites. During the breeding season falcons undertook extensive excursions across both sea and land (females: 159 +/- 288, males: 198 +/- 391 km), often reaching areas far from the colony and routinely encountering wind farms. In Sardinia, 10.2% of the region's turbines were within the ICA. Around 53% of the locations during foraging excursions fell within the turbine rotor-swept zone (RSZ), and accelerometer data revealed that peak flight activity of falcons coincided with peak wind intensity, the moment when turbines are most likely to be operational. Overall, results suggested that Eleonora's Falcons are highly mobile during the breeding season and that wind farms pose a potential threat. To aid in spatial planning and management, especially considering the predicted increase in offshore wind farms in the area, we provide the identified ICA freely available for download.
This work reports on the design and outcomes of a large-scale interlaboratory comparison dedicated to narrow-band ElectroMagnetic Field (EMF) measurements of 5G New Radio (NR) signals. The campaign, conducted under controlled yet realistic conditions on a private FR1 5G network, involved 34 laboratories and aimed to validate the application of Maximum Power Extrapolation (MPE) procedures. Participants employed Vector Signal Analyzers (VSAs) to implement four distinct methodologies: Channel Power (CHP) estimation under full traffic forcing, Zero-Span (ZS) acquisition, direct Synchronization Signal Block (SSB) demodulation, and full-frame demodulation for Physical Downlink Shared CHannel (PDSCH) resource-level analysis. Statistical evaluation based on ISO 13528 and ISO 17043 revealed high consistency among methods, with robust averages converging within 5% and z-score dispersion generally below 2, even considering the intrinsic variability of 5G signals and the challenges in correctly assessing measurement uncertainty. These findings confirm the reliability of narrow-band approaches for compliance assessment and provide a validated framework for harmonized EMF monitoring in next-generation mobile networks.
