ALBERT

Description: Blooms of Zygnematophycean “glacier algae” lower the bare ice albedo of the Greenland Ice Sheet (GrIS), amplifying summer energy absorption at the ice surface and enhancing meltwater runoff from the largest cryospheric contributor to contemporary sea-level rise. Here, we provide a step change in current understanding of algal-driven ice sheet darkening through quantification of the photophysiological mechanisms that allow glacier algae to thrive on and darken the bare ice surface. Significant secondary phenolic pigmentation (11 times the cellular content of chlorophylla) enables glacier algae to tolerate extreme irradiance (up to ∼4,000 µmol photons⋅m−2⋅s−1) while simultaneously repurposing captured ultraviolet and short-wave radiation for melt generation. Total cellular energy absorption is increased 50-fold by phenolic pigmentation, while glacier algal chloroplasts positioned beneath shading pigments remain low-light–adapted (Ek∼46 µmol photons⋅m−2⋅s−1) and dependent upon typical nonphotochemical quenching mechanisms for photoregulation. On the GrIS, glacier algae direct only ∼1 to 2.4% of incident energy to photochemistry versus 48 to 65% to ice surface melting, contributing an additional ∼1.86 cm water equivalent surface melt per day in patches of high algal abundance (∼104cells⋅mL−1). At the regional scale, surface darkening is driven by the direct and indirect impacts of glacier algae on ice albedo, with a significant negative relationship between broadband albedo (Moderate Resolution Imaging Spectroradiometer [MODIS]) and glacier algal biomass (R2= 0.75,n= 149), indicating that up to 75% of the variability in albedo across the southwestern GrIS may be attributable to the presence of glacier algae.

Description: Subglacial Antarctic aquatic environments are important targets for scientific exploration due to the unique ecosystems they support and their sediments containing palaeoenvironmental records. Directly accessing these environments while preventing forward contamination and demonstrating that it has not been introduced is logistically challenging. The Whillans Ice Stream Subglacial Access Research Drilling (WISSARD) project designed, tested and implemented a microbiologically and chemically clean method of hot-water drilling that was subsequently used to access subglacial aquatic environments. We report microbiological and biogeochemical data collected from the drilling system and underlying water columns during sub-ice explorations beneath the McMurdo and Ross ice shelves and Whillans Ice Stream. Our method reduced microbial concentrations in the drill water to values three orders of magnitude lower than those observed in Whillans Subglacial Lake. Furthermore, the water chemistry and composition of microorganisms in the drill water were distinct from those in the subglacial water cavities. The submicron filtration and ultraviolet irradiation of the water provided drilling conditions that satisfied environmental recommendations made for such activities by national and international committees. Our approach to minimizing forward chemical and microbiological contamination serves as a prototype for future efforts to access subglacial aquatic environments beneath glaciers and ice sheets.

Description: Melting of the Greenland Ice Sheet (GrIS) is the largest single contributor to eustatic sea level and is amplified by the growth of pigmented algae on the ice surface, which increases solar radiation absorption. This biological albedo-reducing effect and its impact upon sea level rise has not previously been quantified. Here, we combine field spectroscopy with a radiative-transfer model, supervised classification of unmanned aerial vehicle (UAV) and satellite remote-sensing data, and runoff modelling to calculate biologically driven ice surface ablation. We demonstrate that algal growth led to an additional 4.4–6.0 Gt of runoff from bare ice in the south-western sector of the GrIS in summer 2017, representing 10 %–13 % of the total. In localized patches with high biomass accumulation, algae accelerated melting by up to 26.15±3.77 % (standard error, SE). The year 2017 was a high-albedo year, so we also extended our analysis to the particularly low-albedo 2016 melt season. The runoff from the south-western bare-ice zone attributed to algae was much higher in 2016 at 8.8–12.2 Gt, although the proportion of the total runoff contributed by algae was similar at 9 %–13 %. Across a 10 000 km2 area around our field site, algae covered similar proportions of the exposed bare ice zone in both years (57.99 % in 2016 and 58.89 % in 2017), but more of the algal ice was classed as “high biomass” in 2016 (8.35 %) than 2017 (2.54 %). This interannual comparison demonstrates a positive feedback where more widespread, higher-biomass algal blooms are expected to form in high-melt years where the winter snowpack retreats further and earlier, providing a larger area for bloom development and also enhancing the provision of nutrients and liquid water liberated from melting ice. Our analysis confirms the importance of this biological albedo feedback and that its omission from predictive models leads to the systematic underestimation of Greenland's future sea level contribution, especially because both the bare-ice zones available for algal colonization and the length of the biological growth season are set to expand in the future.

Description: One of the primary controls upon the melting of the Greenland Ice Sheet (GrIS) is albedo, a measure of how much solar radiation that hits a surface is reflected without being absorbed. Lower-albedo snow and ice surfaces therefore warm more quickly. There is a major difference in the albedo of snow-covered versus bare-ice surfaces, but observations also show that there is substantial spatio-temporal variability of up to ∼0.4 in bare-ice albedo. Variability in bare-ice albedo has been attributed to a number of processes including the accumulation of light-absorbing impurities (LAIs) and the changing physical properties of the near-surface ice. However, the combined impact of these processes upon albedo remains poorly constrained. Here we use field observations to show that pigmented glacier algae are ubiquitous and cause surface darkening both within and outside the south-west GrIS “dark zone” but that other factors including modification of the ice surface by algal bloom presence, surface topography and weathering crust state are also important in determining patterns of daily albedo variability. We further use observations from an unmanned aerial system (UAS) to examine the scale gap in albedo between ground versus remotely sensed measurements made by Sentinel-2 (S-2) and MODIS. S-2 observations provide a highly conservative estimate of algal bloom presence because algal blooms occur in patches much smaller than the ground resolution of S-2 data. Nevertheless, the bare-ice albedo distribution at the scale of 20 m×20 m S-2 pixels is generally unimodal and unskewed. Conversely, bare-ice surfaces have a left-skewed albedo distribution at MODIS MOD10A1 scales. Thus, when MOD10A1 observations are used as input to energy balance modelling, meltwater production can be underestimated by ∼2 %. Our study highlights that (1) the impact of the weathering crust state is of similar importance to the direct darkening role of light-absorbing impurities upon ice albedo and (2) there is a spatial-scale dependency in albedo measurement which reduces detection of real changes at coarser resolutions.

Description: Trace elements sustain biological productivity, yet the significance of trace element mobilization and export in subglacial runoff from ice sheets is poorly constrained at present. Here, we present size-fractionated (0.02, 0.22, and 0.45 µm) concentrations of trace elements in subglacial waters from the Greenland Ice Sheet (GrIS) and the Antarctic Ice Sheet (AIS). Concentrations of immobile trace elements (e.g., Al, Fe, Ti) far exceed global riverine and open ocean mean values and highlight the importance of subglacial aluminosilicate mineral weathering and lack of retention of these species in sediments. Concentrations are higher from the AIS than the GrIS, highlighting the geochemical consequences of prolonged water residence times and hydrological isolation that characterize the former. The enrichment of trace elements (e.g., Co, Fe, Mn, and Zn) in subglacial meltwaters compared with seawater and typical riverine systems, together with the likely sensitivity to future ice sheet melting, suggests that their export in glacial runoff is likely to be important for biological productivity. For example, our dissolved Fe concentration (20,900 nM) and associated flux values (1.4 Gmol y−1) from AIS to the Fe-deplete Southern Ocean exceed most previous estimates by an order of magnitude. The ultimate fate of these micronutrients will depend on the reactivity of the dominant colloidal size fraction (likely controlled by nanoparticulate Al and Fe oxyhydroxide minerals) and estuarine processing. We contend that ice sheets create highly geochemically reactive particulates in subglacial environments, which play a key role in trace elemental cycles, with potentially important consequences for global carbon cycling.

Description: Abstract

Description: This data publication is supplementary material to McCutcheon et al. (2021): "Melting of the Greenland Ice Sheet is a leading cause of land-ice mass loss and cryosphere-attributed sea level rise. Blooms of pigmented glacier ice algae lower ice albedo and accelerate surface melting in the ice sheet’s southwest sector. Although glacier ice algae cause up to 13% of the surface melting in this region, the controls on bloom development remain poorly understood. Here we show a direct link between mineral phosphorus in surface ice and glacier ice algae biomass through the quantification of solid and fluid phase phosphorus reservoirs in surface habitats across the southwest ablation zone of the ice sheet. We demonstrate that nutrients from mineral dust likely drive glacier ice algal growth, and thereby identify mineral dust as a secondary control on ice sheet melting." Tables included in this data publication: Supplementary Table 1. Locations, dates and sample types collected for particulate analyses. Sites 4a and 4b were the base camp locations for 2016 and 2017, respectively. Supplementary Table 2. Results of a Tukey HSD test with a 95% family-wise confidence interval for Fv/Fm measurements made at 24 h and 120 h in the nutrient addition experiment. Supplementary Table 3. Results of a Tukey HSD test with a 95% family-wise confidence interval for rETRmax measurements made at 24 h and 120 h in the nutrient addition experiment. Supplementary Table 4. Glacier algal cell concentrations (cells·mL-1) at the end of the 120 h nutrient incubation experiment. Glacier algae assemblage used for the incubations had an initial mean cell concentration of 8.0 ± 2.1  103 cells·mL-1. Supplementary Table 5. Carbon, nitrogen, and phosphorus content of solid LAPs collected from melted surface ice. TC: total carbon. TOC: total organic carbon, IC: inorganic carbon, Pexch: exchangeable/loosely bound phosphorus, Pmin: mineral phosphorus, Porg: organic phosphorus. Supplementary Table 6. Mineral phase abundances in 2016 and 2017 particulate samples as determined by Rietveld refinement with powder X-ray diffraction data. Abundances given as weight percent of total mineral dust (n=20). Supplementary Table 7. Mineral class abundances in high algal biomass (Hbio) ice sampled across the ablation zone in 2016. Values listed in weight percent of total mineral dust % (+/- standard error where applicable). Two-sided t-test comparing of mineral class abundances between site 3 and 4a. Supplementary Table 8. Major cation and anion concentrations in the fluid phase and pH, conductivity and total dissolved solids (TDS) of supraglacial stream water and melted ice and snow samples. LOD: level of detection, LOQ: level of quantification, ND: no data. Supplementary Table 9. Number of raw and processed sequences after each quality filtering step for 16S, ITS2 and 18S. Supplementary Table 10. Table shows the full bacterial community composition with the taxonomic assignments of each ASV on the lowest possible level. Values represent the relative abundances of the 16S ASVs in percentage of the total number of sequences and collapsed on the species level. Values are rounded to one decimal place, thus “〈” represents relative abundance values 〈 0.05 and 〉 0. Supplementary Table 11. Table shows the full eukaryotic community composition collapsed into higher eukaryotic taxonomic groups. Values represent the relative abundance of the 18S ASVs in percentage of the total number of sequences and collapsed on the species level. Values are rounded to one decimal place, thus “〈” represents relative abundance 〈 0.05 and 〉 0. Supplementary Table 12. Table shows the fungal community composition with the taxonomic assignments of the ten most abundant ASV on the lowest possible level. The representative sequences were blasted against NCBI and the closest accession number with the respective similarity were recorded. If several hits shared the similarity one hit was chosen as an example (“e.g.”). Values represent the relative abundance of the ITS2 ASVs in percentage of the total number of sequences. Values are rounded to one decimal place, thus “〈” represents relative abundance values 〈 0.05 and 〉 0. Supplementary Table 13. Table shows the full algal community composition with the taxonomic assignments of each ASV on the lowest possible level. Values represent the relative abundance of the 18S ASVs in percentage of the total number of sequences. All ASVs were blasted against NCBI and the closest accession number with the respective similarity were recorded. If several hits shared the similarity one hit was chosen as an example (“e.g.”). Values are rounded to one decimal place, hence “〈” represents relative abundance 〈 0.05 and 〉 0. *Based on light microscopic identifications in Lutz et al. (2018), this ASV likely represents Mesotaenium sp. (99.4% similarity with M. berggrenii var. alaskana) and not Ancylonema nordenskioeldii despite the slightly higher similarity (99.6%). Supplementary Table 14. Rare Earth Element (REE) analysis concentrations (µg·g-1) for the mineral dust in particulate samples.

Description: TechnicalInfo

Description: Scanning electron microscopy data was collected by J. McCutcheon using a Hitatchi 8230 SEM at the Leeds Electron Microscopy and Spectroscopy Centre (LEMAS), University of Leeds, UK. X-ray diffraction was conducted by J. McCutcheon using a Bruker D8 Advance Eco X-ray diffractometer (Bruker, Billerica, USA) with a Cu source at the University of Leeds, UK. ICP-MS was conducted by S. Reid using a Thermo Fisher iCAPQc ICP-MS at the University of Leeds, UK. Phosphorus was measured either using segmented flow-injection analysis (AutoAnalyser3, Seal Analytical), or for samples containing lower concentrations of phosphorus by A. Stockdale, using a 100 cm WPI Liquid Waveguide Capillary Cell in conjunction with an Ocean Optics USB2000+ spectrophotometer. Both analyses were conducted at the University of Leeds, UK. Ion chromatography was conducted by A. Viet-Hillebrand at the German Research Centre for Geosciences, Potsdam, Germany using a conductivity detector on a Dionex ICS 3000 system, equipped with an AS 11 HC Dionex analytical column. Carbon and nitrogen analysis was conducted by B. Plessen and S. Pinkerneil at German Research Centre for Geosciences, Potsdam, Germany using an NC2500 Carlo Erba elemental analyzer. Amplicon libraries were sequenced on the Illumina MiSeq using paired 300-bp reads at the University of Bristol Genomics Facility, Bristol, UK. Rare Earth element concentrations were measured by A. Vanderstraeten using HR-ICP-MS (ThermoFisher Element 2) at the Vrije Universiteit Brussel, Belgium. Particle size distribution was measured by K. Jurkschat using a DC24000 CPS disc centrifuge at Oxford Materials Characterisation Services, Oxford, UK.