We present the first estimate of green snow algae community biomass and distribution along the Antarctic Peninsula. Sentinel 2 imagery supported by two field campaigns revealed 1679 snow algae blooms, seasonally covering 1.95 × 10⁶ m² and equating to 1.3 × 10³ tonnes total dry biomass. Ecosystem range is limited to areas with average positive summer temperatures, and distribution strongly influenced by marine nutrient inputs, with 60% of blooms less than 5 km from a penguin colony. A warming Antarctica may lose a majority of the 62% of blooms occupying small, low-lying islands with no high ground for range expansion. However, bloom area and elevation were observed to increase at lower latitudes, suggesting that parallel expansion of bloom area on larger landmasses, close to bird or seal colonies, is likely. This increase is predicted to outweigh biomass lost from small islands, resulting in a net increase in snow algae extent and biomass as the Peninsula warms.

Antarctica plays a central role in regulating global climatic and oceanographic patterns and is an integral part of global climate change discussions. The functioning of Antarctica's terrestrial ecosystems is dominated by poikilohydric cryptogams such as lichens, bryophytes, eukaryotic algae, and cyanobacteria and there are only two native species of vascular plants. Antarctica's vegetation is highly adapted to the region's extreme conditions but, at the same time, it is potentially highly susceptible to climatic fluctuations. Biological responses to shifts in temperature, water availability, wind patterns, snow, and ice cover are complex, taxa‐specific and act on different temporal and spatial scales. In maritime Antarctica, where warming and mass loss of outlet glaciers have been mainly observed, the vegetation is expected to show increases in productivity, abundance, and cover. In continental Antarctica, observational and experimental evidence is still sparse, but it is pointing toward even drier and harsher conditions for survival. We need more information on what the observed and predicted changes in Antarctic vegetation are for different regions and ecosystems. This will inform us how environmental change and human impact will shape the future of these ecosystems, and whether the speed and magnitude of change have habitat‐specific effects and implications. Antarctica's unique ecosystems are changing and in this review, we describe the current situation, tools to measure, and evaluate change and how change is likely to look in the future.This article is categorized under: Climate, Ecology, and Conservation > Observed Ecological Changes Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change Climate, Ecology, and Conservation > Modeling Species and Community Interactions Assessing Impacts of Climate Change > Observed Impacts of Climate Change

Terrestrial vegetation communities across Antarctica are characteristically sparse, presenting a challenge for mapping their occurrence using remote sensing at the continent scale. At present there is no continent-wide baseline record of Antarctic vegetation, and large-scale area estimates remain unquantified. With local vegetation distribution shifts now apparent and further predicted in response to environmental change across Antarctica, it is critical to establish a baseline to document these changes. Here we present a 10 m-resolution map of photosynthetic life in terrestrial and cryospheric habitats across the entire Antarctic continent, maritime archipelagos and islands south of 60° S. Using Sentinel-2 imagery (2017–2023) and spectral indices, we detected terrestrial green vegetation (vascular plants, bryophytes, green algae) and lichens across ice-free areas, and cryospheric green snow algae across coastal snowpacks. The detected vegetation occupies a total area of 44.2 km², with over half contained in the South Shetland Islands, altogether contributing just 0.12% of the total ice-free area included in the analysis. Due to methodological constraints, dark-coloured lichens and cyanobacterial mats were excluded from the study. This vegetation map improves the geospatial data available for vegetation across Antarctica, and provides a tool for future conservation planning and large-scale biogeographic assessments.

Membrane proteins are involved in numerous essential cell processes, including transport, gene regulation, motility, and metabolism. To function properly, they must be inserted into the membrane and folded correctly. YidC, an essential protein in Escherichia coli with homologues in other bacteria, Archaea , mitochondria, and chloroplasts, functions by incompletely understood mechanisms in the insertion and folding of certain membrane proteins. Using a genome-scale approach, we identified 69 E. coli membrane proteins that, in the absence of YidC, exhibited aberrant localization by microscopy. Further examination of a subset revealed biochemical defects in membrane insertion in the absence of YidC, indicating their dependence on YidC for proper membrane insertion or folding. Membrane proteins possessing an unfavorable distribution of positively charged residues were significantly more likely to depend on YidC for membrane insertion. Correcting the charge distribution of a charge-unbalanced YidC-dependent membrane protein abrogated its requirement for YidC, while perturbing the charge distribution of a charge-balanced YidC-independent membrane protein rendered it YidC dependent, demonstrating that charge distribution can be a necessary and sufficient determinant of YidC dependence. These findings provide insights into a mechanism by which YidC promotes proper membrane protein biogenesis and suggest a critical function of YidC in all organisms and organelles that express it. IMPORTANCE Biological membranes are fundamental components of cells, providing barriers that enclose the cell and separate compartments. Proteins inserted into biological membranes serve critical functions in molecular transport, molecular partitioning, and other essential cell processes. The mechanisms involved in the insertion of proteins into membranes, however, are incompletely understood. The YidC protein is critical for the insertion of a subset of proteins into membranes across an evolutionarily wide group of organisms. Here we identify a large group of proteins that depend on YidC for membrane insertion in Escherichia coli , and we identify unfavorable distribution of charge as an important determinant of YidC dependence for proper membrane insertion.

Snow algae are an important group of terrestrial photosynthetic organisms in Antarctica, where they mostly grow in low lying coastal snow fields. Reliable observations of Antarctic snow algae are difficult owing to the transient nature of their blooms and the logistics involved to travel and work there. Previous studies have used Sentinel 2 satellite imagery to detect and monitor snow algal blooms remotely, but were limited by the coarse spatial resolution and difficulties detecting red blooms. Here, for the first time, we use high-resolution WorldView multispectral satellite imagery to study Antarctic snow algal blooms in detail, tracking the growth of red and green blooms throughout the summer. Our remote sensing approach was developed alongside two Antarctic field seasons, where field spectroscopy was used to build a detection model capable of estimating cell density. Global Positioning System (GPS) tagging of blooms and in situ life cycle analysis was used to validate and verify our model output. WorldView imagery was then used successfully to identify red and green snow algae on Anchorage Island (Ryder Bay, 67°S), estimating peak coverage to be 9.48 × 10⁴ and 6.26 × 10⁴ m², respectively. Combined, this was greater than terrestrial vegetation area coverage for the island, measured using a normalized difference vegetation index. Green snow algae had greater cell density and average layer thickness than red blooms (6.0 × 10⁴ vs. 4.3 × 10⁴ cells ml⁻¹) and so for Anchorage Island we estimated that green algae dry biomass was over three times that of red algae (567 vs. 180 kg, respectively). Because the high spatial resolution of the WorldView imagery and its ability to detect red blooms, calculated snow algal area was 17.5 times greater than estimated with Sentinel 2 imagery. This highlights a scaling problem of using coarse resolution imagery and suggests snow algal contribution to net primary productivity on Antarctica may be far greater than previously recognized.

In intensively cultivated landscapes, many archaeological remains are buried under the ploughed soil, and detection depends on crop proxies that express subsurface features. Traditionally these proxies have been documented in visible light as contrasting areas of crop development commonly known as cropmarks. However, it is recognised that reliance on the visible electromagnetic spectrum has inherent limitations on what can be documented, and multispectral and thermal sensors offer the potential to greatly improve our ability to detect buried archaeological features in agricultural fields. The need for this is pressing, as ongoing agricultural practices place many subsurface archaeological features increasingly under threat of destruction. The effective deployment of multispectral and thermal sensors, however, requires a better understanding of when they may be most effective in documenting archaeologically induced responses. This paper presents the first known use of the FLIR Vue Pro-R thermal imager and Red Edge-M for exploring crop response to archaeological features from two UAV surveys flown in May and June 2019 over a known archaeological site. These surveys provided multispectral imagery, which was used to create vegetation index (VI) maps, and thermal maps to assess their effectiveness in detecting crop responses in the temperate Scottish climate. These were visually and statistically analysed using a Mann Whitney test to compare temperature and reflectance values. While the study was compromised by unusually damp conditions which reduced the potential for cropmarking, the VIs (e.g., Normalised Difference Vegetation Index, NDVI) did show potential to detect general crop stress across the study site when they were statistically analysed. This demonstrates the need for further research using multitemporal data collection across case study sites to better understand the interactions of crop responses and sensors, and so define appropriate conditions for large-area data collection. Such a case study-led multitemporal survey approach is an ideal application for UAV-based documentation, especially when “perfect” conditions cannot be guaranteed.