Albedo plays a key role in regulating the absorption of solar radiation within ice surfaces and hence strongly regulates the production of meltwater. A combination of Landsat and Sentinel 2 data provides the longest continuous medium resolution (10-30 m) earth surface observatory records. An albedo product (harmonized satellite albedo, hereafter HSA) has already been developed and validated for the Greenland Ice Sheet (GrIS), using harmonized Landsat 4-8 and Sentinel 2 datasets. In this paper, the HSA was validated for various Arctic and alpine glaciers and ice caps using measurements. We determine the optimal spatial window size in point-to-pixel analysis, the best practices in evaluating remote sensing algorithms with groundtruth data, and cross sensor comparison of the Landsat 9 (L9) and Landsat 8 (L8) data. The impact of the spatial window size on measured ice surface homogeneity and albedo validation was analysed at both local and regional scales. Homogeneity statistics calculated from the grey-level co-occurrence matrix (GLCM) suggest that the ice surface becomes more homogeneous as the image resolution becomes coarser. The optimal spatial window size was found to be 90 m, based on maximizing the statistical and graphical measures while minimizing the root mean square error and bias. HSAs generally agree closely with albedo measurements (e.g. Pearson's R ranges from 0.68 to 0.92) across various Arctic and alpine glaciers and ice caps. Cross sensor differences between L9 and L8 are minor, and we suggest that no harmonization is necessary to add L9 to our HSA product.

Under climatic warming, glaciers are becoming a secondary source of atmospheric contaminants originally released into the environment decades ago. This phenomenon has been well-documented for glaciers near emission sources. However, less is known about polar ice sheets and ice caps. Radionuclides are one of the contaminants that can be remobilised through ice melting and accumulate in cryoconite material on the surface of glaciers. To understand the cycling of radionuclides in polar glacial contexts, we evaluate the radioactivity of cryoconite samples from Flade Isblink, a High Arctic ice cap in northeast Greenland. The measured radioactivity is among the highest reported across the High Arctic and the highest from Greenland. The high variability observed among the samples is explained by considering the different macroscopic features of single cryoconite deposits. The radioactivity source is compatible with the stratospheric reservoir established during atmospheric nuclear tests and with weapons-grade fissile fuel, likely originating from Novaya Zemlya proving grounds. This study shows that the ability of cryoconite to accumulate radioactivity in remote areas is undisputed, highlighting the need for a deeper understanding of the remobilisation of radioactive species in polar glacial contexts.

Microplastic pollution and climate change, the two seemingly distinct phenomena of global concern, are interconnected through various pathways. The connecting links between the two include the biological carbon pumps in the oceans, the sea ice, the plastisphere involved in biogeochemical cycling and the direct emissions of greenhouse gases from microplastics. On one hand, the presence of microplastics in the water column disrupts the balance of the natural carbon sequestration by affecting the key players in the pumping of carbon, such as the phytoplankton and zooplankton. On the other hand, the effect of microplastics on the sea ice in Polar Regions is two-way, as the ice caps are transformed into sinks and sources of microplastics and at the same time, the microplastics can enhance the melting of ice by reducing the albedo. Microplastics may have more potential than larger plastic fragments to release greenhouse gases (GHGs). Microbe-mediated emission of GHGs from soils is also now altered by the microplastics present in the soil. Plastisphere, the emerging microbiome in aquatic environments, can also contribute to climate change as it hosts complex networks of microbes, many of which are involved in greenhouse gas production. To combat a global stressor like climate change, it needs to be addressed with a holistic approach and this begins with tracing the various stressors like microplastic pollution that can aggravate the impacts of climate change.

Climate change is one of the main factors affecting biodiversity worldwide at an alarming rate. In addition to increases in global extreme weather events, melting of polar ice caps, and subsequent sea level rise, climate change might shift the geographic distribution of species. In recent years, interest in understanding the effects of climate change on species distribution has increased, including species which depend greatly on forest cover for survival, such as strictly arboreal primates. Here, we generate a series of species distribution models (SDMs) to evaluate future projections under different climate change scenarios on the distribution of the black howler monkey (Alouatta pigra), an endemic endangered primate species. Using SDMs, we assessed current and future projections of their potential distribution for three Social Economic Paths (SSPs) for the years 2030, 2050, 2070, and 2090. Specifically, we found that precipitation seasonality (BIO15, 30.8%), isothermality (BIO3, 25.4%), and mean diurnal range (BIO2, 19.7.%) are the main factors affecting A. pigra distribution. The future climate change models suggested a decrease in the potential distribution of A. pigra by projected scenarios (from - 1.23 to - 12.66%). The highly suitable area was the most affected above all in the more pessimist scenario most likely related to habitat fragmentation. Our study provides new insights into the potential future distribution and suitable habitats of Alouatta pigra. Such information could be used by local communities, governments, and non-governmental organizations for conservation planning of this primate species.

Land cover responses to climate change must be quantified for understanding Arctic climate, managing Arctic water resources, maintaining the health and livelihoods of Arctic societies and for sustainable economic development. This need is especially pressing in Greenland, where climate changes are amongst the most pronounced of anywhere in the Arctic. Ice loss from the Greenland Ice Sheet and from glaciers and ice caps has increased since the 1980s and consequently the proglacial parts of Greenland have expanded rapidly. Here we determine proglacial land cover changes at 30 m spatial resolution across Greenland during the last three decades. Besides the vastly decreased ice cover (- 28,707 km ± 9767 km), we find a doubling in total areal coverage of vegetation (111% ± 13%), a quadrupling in wetlands coverage (380% ± 29%), increased meltwater (15% ± 15%), decreased bare bedrock (- 16% ± 4%) and increased coverage of fine unconsolidated sediment (4% ± 13%). We identify that land cover change is strongly associated with the difference in the number of positive degree days, especially above 6 °C between the 1980s and the present day. Contrastingly, absolute temperature increase has a negligible association with land cover change. We explain that these land cover changes represent local rapid and intense geomorphological activity that has profound consequences for land surface albedo, greenhouse gas emissions, landscape stability and sediment delivery, and biogeochemical processes.

Mosses are vital components of ecosystems, exhibiting remarkable adaptability across diverse habitats from deserts to polar ice caps. Sanionia uncinata (Hedw.) Loeske, a dominant Antarctic moss survives extreme environmental condition through perennial lifecycles involving growth and dormancy alternation. This study explores genetic controls and molecular mechanisms enabling S. uncinata to cope with seasonality of the Antarctic environment. We analysed the seasonal transcriptome dynamics of S. uncinata collected monthly from February 2015 to January 2016 in King George Island, Antarctica. Findings indicate that genes involved in plant growth were predominantly upregulated in Antarctic summer, while those associated with protein synthesis and cell cycle showed marked expression during the winter-to-summer transition. Genes implicated in cellular stress and abscisic acid signalling were highly expressed in winter. Further, validation included a comparison of the Antarctic field transcriptome data with controlled environment simulation of Antarctic summer and winter temperatures, which revealed consistent gene expression patterns in both datasets. This proposes a seasonal gene regulatory model of S. uncinate to understand moss adaptation to extreme environments. Additionally, this data set is a valuable resource for predicting genetic responses to climatic fluctuations, enhancing our knowledge of Antarctic flora's resilience to global climate change.

Organophosphate esters (OPEs) have been used as flame retardants, plasticizers, and anti-foaming agents over the past several decades. Of particular interest is the long range transport potential of OPEs given their ubiquitous detection in Arctic marine air. Here we report 19 OPE congeners in ice cores drilled on remote icefields and ice caps in the Canadian high Arctic. A multi-decadal temporal profile was constructed in the sectioned ice cores representing a time scale spanning the 1970s to 2014-16. In the Devon Ice Cap record, the annual total OPE (∑OPEs) depositional flux for all of 2014 was 81 μg m, with the profile dominated by triphenylphosphate (TPP, 9.4 μg m) and tris(2-chloroisopropyl) phosphate (TCPP, 42 μg m). Here, many OPEs displayed an exponentially increasing depositional flux including TCPP which had a doubling time of 4.1 ± 0.44 years. At the more northern site on Mt. Oxford icefield, the OPE fluxes were lower. Here, the annual ∑OPEs flux in 2016 was 5.3 μg m, dominated by TCPP (1.5 μg m) but also tris(2-butoxyethyl) phosphate (1.5 μg m TBOEP). The temporal trend for halogenated OPEs in the Mt. Oxford icefield is bell-shaped, peaking in the mid-2000s. The observation of OPEs in remote Arctic ice cores demonstrates the cryosphere as a repository for these substances, and supports the potential for long-range transport of OPEs, likely associated with aerosol transport.

Flow cytometry is a potential technology for life detection on icy moons (such as Enceladus and Europa) and on the polar ice caps of Mars. We developed a method for using flow cytometry to positively identify four classes of biomarkers using exogenous fluorescent stains: nucleic acids, proteins, carbohydrates, and lipids. We demonstrated the effectiveness of exogenous stains with six known organisms and known abiotic material and showed that the cytometer is easily able to distinguish between the known organisms and the known abiotic material using the exogenous stains. To simulate a life-detection experiment on an icy world lander, we used six natural samples with unknown biotic and abiotic content. We showed that flow cytometry can identify all four biomarkers using the exogenous stains and can separate the biotic material from the known abiotic material on scatter plots. Exogenous staining techniques would likely be used in conjunction with intrinsic fluorescence, clustering, and sorting for a more complete and capable life-detection instrument on an icy moon lander.

Glaciers host ecosystems comprised of biodiverse and active microbiota. Among glacial ecosystems, less is known about the ecology of ice caps since most studies focus on valley glaciers or ice sheet margins. Previously we detailed the microbiota of one such high Arctic ice cap, focusing on cryoconite as a microbe-mineral aggregate formed by cyanobacteria. Here, we employ metabolomics at the scale of an entire ice cap to reveal the major metabolic pathways prevailing in the cryoconite of Foxfonna, central Svalbard. We reveal how geophysical and biotic processes influence the metabolomes of its resident cryoconite microbiota. We observed differences in amino acid, fatty acid, and nucleotide synthesis across the cap reflecting the influence of ice topography and the cyanobacteria within cryoconite. Ice topography influences central carbohydrate metabolism and nitrogen assimilation, whereas bacterial community structure governs lipid, nucleotide, and carotenoid biosynthesis processes. The prominence of polyamine metabolism and nitrogen assimilation highlights the importance of recycling nitrogenous nutrients. To our knowledge, this study represents the first application of metabolomics across an entire ice mass, demonstrating its utility as a tool for revealing the fundamental metabolic processes essential for sustaining life in supraglacial ecosystems experiencing profound change due to Arctic climate change-driven mass loss.

The Northern Sea Route (NSR) makes travel between Europe and Asia shorter and quicker than a southern transit via the Strait of Malacca and Suez Canal. It provides greater access to Arctic resources such as oil and gas. As global warming accelerates, melting Arctic ice caps are likely to increase traffic in the NSR and enhance its commercial viability. Due to the harsh Arctic environment imposing threats to the safety of ship navigation, it is necessary to assess Arctic navigation risk to maintain shipping safety. Currently, most studies are focused on the conventional assessment of the risk, which lacks the validation based on actual data. In this study, actual data about Arctic navigation environment and related expert judgments were used to generate a structured data set. Based on the structured data set, extreme gradient boosting (XGBoost) and alternative methods were used to establish models for the assessment of Arctic navigation risk, which were validated using cross-validation. The results show that compared with alternative models, XGBoost models have the best performance in terms of mean absolute errors and root mean squared errors. The XGBoost models can learn and reproduce expert judgments and knowledge for the assessment of Arctic navigation risk. Feature importance (FI) and shapley additive explanations (SHAP) are used to further interpret the relationship between input data and predictions. The application of XGBoost, FI, and SHAP is aimed to improve the safety of Arctic shipping using advanced artificial intelligence techniques. The validated assessment enhances the quality and robustness of assessment.