Many authors have studied the biogeography of the Southern Ocean (SO), defined its limits and proposed their division into biogeographical zones and provinces. In this work we analyse the biogeography of sea slugs in a broad sense (Mollusca, Gastropoda, Heterobranchia) in the different areas and zones of the SO below 41°S. Most of the published scientific publications, databases and technical reports where records of benthic sea slugs appear in the SO have been analysed in addition to our own records, cataloguing a total of 355 different benthic species. The following areas and zones of the SO have been considered: Antarctica (Weddell Sea, West Antarctica, Ross Sea, East Antarctica), the sub-Antarctic zone (Falkland Islands, South Georgia Island, South Orkney Islands, South Sandwich Islands, Bouvet Island, Crozet and Prince Edward islands, Kerguelen Islands, Macquarie Island), southern South America (Patagonia/Magellan), Tasmania and New Zealand (South Island). A presence/absence table for all recorded species in the different zones has been compiled, and the differences and similarities between them have been calculated using the Sorensen index. The best representation has been obtained by classifying the zones into five groups: G1 (the four Antarctic zones, South Georgia Island, South Sandwich Islands, South Orkney Islands), G2 (Kerguelen Islands, Crozet and Prince Edward islands and Macquarie Island), G3 (Falkland Islands and Patagonia/Magellan), G4 (Tasmania and New Zealand’s South Island) and G5 (Bouvet Island). In addition, the concordance between the non-hierarchical classification (K-mean) and the hierarchical classification obtained using the WARD and UPGMA cluster analysis methods has been verified. The representative and distinctive species of each of these groups are indicated. In this work, as regards benthic sea slugs, the biogeographical affinities between the Antarctic zones and some of the sub-Antarctic zones are confirmed, as well as between the fauna of these molluscs in the Patagonian/Magallan zone and the Falkland Islands, while the affinities between the other zones need further confirmation when more species records become available.

Maritime Antarctica experiences less extreme environmental conditions than much of the Antarctic continent and has further been impacted by considerable warming in recent decades. While inventories exist of macroscopic Antarctic biodiversity, and there is some information available on culturable microorganisms, much less is known about the presence of other cryptic eukaryotic organisms. DNA metabarcoding provides a method for assigning the DNA of multiple different organisms simultaneously from environmental samples. In this study, we used DNA metabarcoding to investigate the environmental DNA (eDNA) diversity of non-fungal eukaryotic organisms associated with rocks in the South Shetland Islands. Five sampling points were selected from a stratigraphic profile at Mazurek Point, King George Island. Collected rock samples were pulverized, total DNA was extracted and amplicons were generated using ITS2 primers, then these were sequenced using an Illumina MiSeq system. Sequences representing five kingdoms and nine phyla were retrieved. Viridiplantae was the most diverse and abundant group, with 42 assigned taxa, followed by Chromista, with 22 assigned taxa. The precise lithology did not influence the assigned diversity. The majority of assigned taxa are widespread and plausibly present in the area, but some are not known from Antarctica, including some from tropical regions. The latter assignments probably result from the limitations of the databases used, although in some cases they may indicate evidence of anthropogenically associated or naturally dispersed DNA-containing material.

We present a synthesis of marine soft sediment macrofaunal communities from the Vestfold Hills, East Antarctica, spanning historical data (1978–1982) and recent surveys from 47 locations (2010–2021). We examined relationships between environmental conditions, such as sediment properties and sea-ice duration, and community structure and biodiversity. Macrofaunal biodiversity was high, with 148 taxa identified in recent surveys. Community composition varied significantly between locations, influenced primarily by sediment grain size. Sediments ranged from mud to coarse sands, with organic content varying from < 1% to 15%, and locations were classified into four sediment categories: muds, very fine sands, fine sands and medium/coarse sands. Significant differences in community structure were found between sediments groups, but the considerable variability within groups suggests additional influences from factors such as sea ice, depth and stochastic processes. Crustaceans, including amphipods, ostracods and tanaids, dominated communities across all locations. Macrofaunal abundance was highest in muds and very fine sands and declined significantly in coarser sediments. Species-level abundance patterns showed high heterogeneity, with some trends linked to sediment grain size. Areas with abundant large sessile epifauna were associated with higher sediment biodiversity. This study highlights the complexity of environmental factors shaping macrofaunal communities in Antarctic coastal ecosystems.

This study investigates the impact of tourist activities on penguin behaviour on Barrientos Island, an intensively visited site in the Antarctic Peninsula. By simulating tourist presence and activities, we assessed the behavioural responses of two species, Pygoscelis antarcticus and Pygoscelis papua, and their differences with regard to two specific factors: nest position (perimetral/non-perimetral) and nesting site size (large/small). The findings reveal that both species were sensitive to human presence, especially when visitors talked while approaching the nesting sites. We observed greater behavioural differences regarding the position within the colony for gentoo penguins (P. papua). For this species, the size of the nesting sites was also an important factor affecting its response to human presence, with the large nesting sites being less affected. This trend was not shared by chinstrap penguins (P. antarcticus), whose behaviour towards visitors was not affected significantly by either factor. We recommend mitigating tourists’ impact by maintaining their viewing distance at greater than 10 m and by having them move quietly and slowly around these penguin species.

Protecting animals from anthropogenic influences is important in vulnerable ecosystems such as Antarctica. A potential recent activity affecting Antarctic wildlife is the use of unmanned aerial vehicles (UAVs). Previous studies in this area have mainly focused on animal behavioural observations and have reported reactions to UAVs in many cases. To gain insights into the influence of UAVs on physiology (stress hormones) in addition to behavioural reactions, we conducted an experiment on chinstrap penguin chicks (Pygoscelis antarcticus) on the South Shetland Islands (Antarctica) during the breeding season of 2017–2018. Using a small quadcopter UAV, we performed flights over groups of penguin chicks in the early crèche phase using ‘Hard’ and ‘Soft’ treatment setups (15 and 50 m above the penguins, respectively). The behavioural observations revealed clear reactions to the UAV during the Hard treatment, but we could not find an association between such UAV activity and stress hormone levels. As we cannot clearly disentangle the effects of handling during blood sampling and the direct influence of the UAV, we conclude that the physiological impact of overflights at 15 m ranges from no impact to a maximum impact equal to the impact associated with animal handling. During the Soft treatment (UAV overflights at 50 m), no behavioural or physiological effects were detected.

We present a new 1:500 000 geological map of Alexander Island of West Antarctica. The map, combined with recent detrital zircon analysis, defines an updated chronostratigraphy for the Fossil Bluff Group, a Late Jurassic–Cretaceous forearc succession > 8 km in thickness that represents one of the most complete forearc successions globally. The forearc succession overlies and is in faulted contact with the LeMay Group, a late Permian basement accretionary complex that forms part of an extensive array of late Permian accretionary complexes in West Gondwana. The LeMay Group is intruded and overlain by a succession of Late Cretaceous–Palaeogene intermediate to silicic volcanic rocks and granitoid plutons. The uppermost unit on Alexander Island is an episode of Neogene to Quaternary basaltic volcanism associated with ridge-trench collisions and slab window development.

Monitoring snow depth in Antarctica is essential for understanding permafrost dynamics and soil thermal regimes. This study assesses the performance of low-cost, high-resolution, autocleaning ultrasonic sensors (MB7574-SCXL-Maxsonar-WRST7), powered by lithium D-type battery Geoprecision-Box dataloggers, in the South Shetland Islands. Traditional methods for estimating snow thickness, such as air temperature sensors in snow stakes, are economical but involve high maintenance costs and various complexities. To address these issues, we deployed ultrasonic sensors across 12 stations on Livingston and Deception islands from early 2023 to early 2024. Located at altitudes from 15 to 274 m above sea level and with varying wind exposures, these devices demonstrated notable durability and reliability, with only one sensor failure occurring due to structural damage. Data processing involved using an R script to filter out noise, and this process provided accurate hourly snow-depth measurements and revealed significant spatial and altitudinal variability, with depths ranging from 20 to 110 cm. Snow accumulation began in April and peaked in August and October, with major snowfall events contributing temporarily to snow depth but not to long-term accumulation. Our findings suggest that these sensors, as low-cost alternatives, could be integrated into networks such as the Global Terrestrial Network for Permafrost (GTN-P), supporting climate and permafrost studies.