Glacier retreat threatens unique microbial communities and biogeochemical functions confined to glacier surfaces

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Vincent, Masaki Uchida This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8090681/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Glaciers are rapidly retreating under climate warming, with potential loss of unique microbial ecosystems. Here, we investigated bacterial and fungal communities across the glacier surface and foreland of the Arklio Glacier, Canadian High Arctic, using 16S and ITS amplicon sequencing. Both bacterial and fungal communities on the glacier were distinct and largely independent from those in the foreland, indicating limited microbial dispersal and strong environmental filtering. Alpha diversity patterns revealed opposite trends between the two groups: bacterial diversity increased toward the glacier terminus, whereas fungal diversity declined. In the foreland, bacterial diversity peaked around 100 m (~ 20 years post-retreat), while fungal diversity reached a maximum at 20 m, suggesting distinct successional responses to deglaciation. Functional predictions indicated contrasting metabolic strategies: phototrophy dominated on glacier ice, whereas chemoheterotrophy and nitrification prevailed in foreland soils. Together, these results demonstrate that glacier retreat reshapes both microbial composition and function, and underscore how glaciers are threatened reservoirs of microbial biodiversity. Biological sciences/Ecology Earth and environmental sciences/Ecology Earth and environmental sciences/Environmental sciences Biological sciences/Microbiology High Arctic glacier retreat microbial community climate change 16S rRNA ITS1 region Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Glaciers cover nearly 10% of Earth’s land surface 1 and play a crucial role in regulating global climate and hydrological cycles. However, they are strongly affected by environmental change and, in recent decades, have experienced major reductions in area, particularly in the High Arctic 2 – 4 . This loss not only reduces ice mass but also threatens unique microbial habitats in the cryosphere, even in slow-changing systems 5 . Beyond their physical and climatic importance, glaciers also harbor diverse microbial communities that sustain primary production and nutrient turnover in extreme oligotrophic environments 6 . These microbial assemblages form self-sufficient ecosystems within cryoconite holes, ice surfaces, and subglacial niches, where they mediate essential biogeochemical processes such as carbon fixation and nutrient regeneration 7 , 8 . However, accelerated glacier retreat under climate warming is transforming these ecosystems at an unprecedented rate, leading to the potential loss of unique microbial habitats and their associated functions 9 , 10 . Previous studies in Arctic, Antarctic, and alpine regions have demonstrated strong ecological differentiation between microbial communities inhabiting glacier ice and those in deglaciated forelands 11 – 14 , where newly exposed sediments progressively develop into soils colonized by plants and heterotrophic microbes. On glacier surfaces, phototrophic bacteria and algae dominate, fueling primary production through oxygenic photoautotrophy under intense solar radiation and nutrient limitation 15 , 16 . In contrast, foreland communities are typically enriched in heterotrophic and nitrifying taxa that utilize organic matter accumulating with soil formation and vegetation establishment 17 , 18 . This transition from autotrophic to heterotrophic energy pathways represents a fundamental reorganization of carbon and nitrogen cycling following glacier retreat 19 , 20 . Yet, the functional divergence between these two coupled ecosystems – and its implications for biogeochemical feedback – remains poorly quantified, and little attention has been given to micro-fungi, despite their unique functional roles in cryospheric habitats. The Arklio Glacier (80°50′N, 82°50′W) on Ellesmere Island in the Canadian High Arctic, provides an ideal setting to examine this ecological and functional transition. The glacier and its foreland represent a chronosequence of deglaciation, with well-preserved moraines that record successive retreat stages since the Last Glacial Maximum. Although geomorphological and botanical features of this foreland have been characterized, microbial diversity and function remain unexplored. Here, we conducted a comprehensive analysis of bacterial and fungal communities across seven sites spanning the glacier surface and foreland. Using high-throughput amplicon sequencing, SourceTracker, and functional prediction approaches (FAPROTAX and FUNGuild), we aimed to (i) characterize microbial diversity and community composition, (ii) identify habitat-specific functional traits, and (iii) assess how these communities shift across glacier and foreland environments at the Arklio Glacier and its foreland in the Canadian High Arctic. Results Bacterial and archaeal abundances and their diversity patterns The results of the taxonomic composition of 16S rRNA sequences were as follows: At Sites 1–3, Proteobacteria, Cyanobacteriota, Bacteroidota, and Chloroflexi together accounted for more than 70% of the total relative frequency of 16S rRNA gene sequences. At Site 4, Proteobacteria, Bacteroidota, and Chloroflexi were dominant, representing over 70% of the community. At Site 5, Actinobacteriota appeared in addition to Proteobacteria, Cyanobacteriota, Bacteroidota, and Chloroflexi, collectively exceeding 70% of the total relative frequency. At foreland Sites 6 and 7, the relative abundance of Acidobacteriota increased alongside Proteobacteria, Cyanobacteriota, Bacteroidota, Chloroflexi, and Actinobacteriota (Fig. 2 ). For Archaea, the phylum Halobacterota accounted for approximately 0.005% of the relative abundance at Site 3, while Crenarchaeota accounted for about 0.03% at Site 7. Analysis of heatmap data from 16S rRNA sequences indicated that Sites 1–3 displayed largely comparable community profiles; however, Site 3 demonstrated a relatively elevated abundance of Firmicutes in comparison to the other glacier sites (Fig. 3 A). In contrast, Sites 4–7 in the foreland showed broadly similar overall patterns but with site-specific compositional features. At Site 4, Campylobacterota and Hydrogenedentes displayed notably higher relative abundances. At Site 6, Fibrobacterota and Nitrospirota were relatively enriched, whereas at Site 7, Sumeriaeota showed a relatively abundance increase while Deinococcota was lower relative abundance compared to Sites 4–6. Site 5 did not exhibit distinct relative abundance features (Fig. 3 A). The results of the PERMANOVA analysis indicates that there were significant differences in community structure among sites (F = 2.685619, p = 0.023; Fig. 3 B). Based on the SourceTracker analysis of 16S rRNA sequences, ASVs originating from Sites 1–3 (on-glacier) accounted for less than 3.5% of the total sequences detected in Sites 4–7 (foreland). Conversely, ASVs from foreland sites contributed only about 1.5% to the on-glacier communities (Fig. 3 C-D). Alpha diversity indices are summarized in Table S1 . Among the four indices, Shannon, Faith’s phylogenetic diversity (PD), and Observed Features were lowest at Site 4, located immediately beyond the glacier terminus (Fig. 3 E, Fig. S1 ). In contrast, Evenness values remained high (> 0.7) and relatively constant across all sites. Fungal abundances and their diversity patterns The results of the taxonomic composition of fungal communities based on ITS sequences were as follows. At Sites 1–3 (on-glacier sites), Ascomycota, Fungi_phyla_Incertae_sedis and Chytridiomycota were predominant, together accounting for over 70% of the total relative abundance. At Site 4 (at the glacier terminus), Basidiomycota and Ascomycota were dominant, with minor contributions from Mucoromycota and Aphelidiomycota. At Site 5, Ascomycota and Basidiomycota, collectively comprised more than 70% of the community. At Sites 6 and 7, Ascomycota, Basidiomycota, and Fungi phy. Incertae sedis remained dominant. Sanchytriomycota was detected at Sites 1, 2, and 7 (Fig. 4 ). Heatmap visualization of ITS1 region diversity revealed broadly comparable community profiles at Sites 1–3 on the glacier, with notable site-specific variations. Notably, Sordariomycetes exhibited a relatively high frequency at Site 1. Conversely, Dothideomycetes demonstrated comparatively lower abundance at Site 2. In contrast, Sites 3 showcased a significant abundance of Ascomycota, Orbiliomycetes, and Eurotiomycetes (Fig. 5 A). Sites 4–7 in the foreland also shared overall similar patterns, though each site displayed distinct taxonomic characteristics. At Site 4, Sordariomycetes and Agaricomycetes were abundant; Site 5 was dominated by Agaricomycetes; and Sites 6 and 7 showed relatively higher abundances of Ascomycota (Fig. 5 A). The results of the PERMANOVA analysis indicates that there were significant differences in community structure among sites (F = 2.88891, p = 0.036; Fig. 5 B). In the SourceTracker analysis of fungal ITS1 region sequences, OTUs originating from Sites 1 and 3 accounted for less than 1.5% of the total sequences detected in Sites 4–7, while those from Site 2 contributed approximately 4%. Conversely, OTUs from foreland sites (Sites 4–7) were detected at low frequencies in on-glacier communities: less than 1.6% in Sites 5 and 7, around 2.5% in Site 4, and approximately 3.6% in Site 6 (Fig. 5 C-D). Fungal alpha diversity indices are summarized in Table S2 . Site 3 exhibited the lowest values for Shannon, Faith’s phylogenetic diversity (PD), and Observed Features, indicating reduced fungal richness and phylogenetic diversity at this location. However, the Evenness index remained above 0.6 across all sites, with Sites 3 and 5 showing the highest values (Fig. 5 E, Fig. S2 ). Functional prediction of bacterial, archaea and fungal communities In the functional prediction of bacterial and archaea communities by FAPROTAX, the top five predicted functions accounted for more than 70% of the total ASV counts across Sites 1–7 in each site. At Sites 1–3, the top five functions were identical and consisted of phototrophy, photoautotrophy, cyanobacteria, oxygenic photoautotrophy, and chemoheterotrophy. At Sites 4–7, chemoheterotrophy and aerobic chemoheterotrophy alone represented approximately 60% or more of the total ASV counts in each site. Chemoheterotrophy appeared consistently among the top five predicted functions at all sites (Table S3 ). For fungal communities, the top five OTUs at each site accounted for more than 60% of the total OTU abundance. Functional guild prediction using FUNGuild showed that a large number of OTUs taxonomically classified as Fungi or Fungi_phy_Incertae_sedis could not be functionally annotated. Among the functionally assigned OTUs, the dominant guilds varied by site. At Site 1, Saprotroph and Pathotroph were dominant; at Site 2, Saprotroph and Saprotroph-Symbiotroph were most abundant. Site 3 was characterized by Lichenized Microfungi (Symbiotroph) and Chytrid Microfungi (Algal Parasite). At Site 4, Microfungi classified as Saprotroph and Chytrid Microfungi as Pathotroph-Saprotroph predominated. At Site 5, Corticioid Fungi (Algal Parasite) and Microfungi (Saprotroph) were prevalent, while at Site 6, Corticioid Fungi (Ectomycorrhizal) and Microfungi (Pathotroph-Saprotroph) dominated. Finally, Site 7 was characterized by Microfungi (Saprotroph) and Corticioid Microfungi (Ectomycorrhizal) (Table S4 ). Discussion Results of 16S rRNA sequencing analyzed through taxonomy, heatmaps and PERMANOVA revealed significant differences between on-glacier and foreland bacterial and archaea assemblages (Fig. 2 , Fig. 3 A-B), and SourceTracker analysis further indicated that the two communities were largely independent with minimal overlap (Fig. 3 C-D). On the glacier, Shannon, Faith PD, and Observed Feature indices increased toward the terminus, suggesting gradual enrichment of microbial diversity. In the foreland, these indices initially decreased just beyond the terminus but peaked at ~ 100 m, corresponding to ca. 20 years after glacier retreat, before stabilizing. Evenness remained stable (> 0.7) across habitats (Fig. 3 E; Fig. S1 ). These results demonstrate that dispersal between glacier and foreland habitats is limited, with each sustaining unique communities shaped by contrasting environmental conditions and hydrological isolation 7 . Functional predictions of bacteria and archaea revealed habitat-specific metabolic potentials. On the glacier, phototrophic-associated indicators such as cyanobacteria and oxygenic photoautotrophy dominated, suggesting that primary production is maintained by light-dependent processes under nutrient-poor, high-radiation conditions 5 , 26 . In contrast, ASV detection in the foreland was dominated by two functions: chemoheterotrophy and aerobic chemoheterotrophy. This pattern reflects a metabolic shift toward heterotrophic energy acquisition following the accumulation of organic matter after glacier retreat 27 , 28 . Moreover, nitrification-related functions, including aerobic ammonia and nitrite oxidation, were detected at low frequencies and mainly in foreland soils, suggesting the onset of nitrogen cycling during early soil development 21 , 29 . Nevertheless, trace signals of nitrogen fixation and nitrate reduction were also detected in glacier surface samples, indicating that limited nitrogen transformations may occur even under oligotrophic ice conditions. Previous studies have reported that such processes can vary considerably among glacier systems – for example, nitrification and denitrification in cryoconite granules (Segawa et al., 2014) and isotopic evidence of nitrogen cycling within glacier interiors (Hattori et al., 2023) – highlighting that while the Arklio Glacier system shows restricted nitrogen activity on ice, it follows the broader pattern of functional differentiation between glaciers and their forelands. 30 , 31 . Consistent with bacterial and archaea assemblages, fungal communities exhibited a similar independence but a contrasting diversity trajectory (Fig. 4 , Fig. 5 A-B). PERMANOVA and SourceTracker analyses confirmed clear separation between glacier and foreland assemblages (Fig. 5 A–D). On the glacier, Shannon, Faith PD, and Observed Feature indices decreased toward the terminus, while in the foreland, diversity peaked around 30 m from the terminus before stabilizing. Evenness remained above 0.6 in both environments, suggesting stable species distribution (Fig. 5 E; Fig. S2 ). These patterns suggest that bacterial, archaeal and fungal communities respond to deglaciation on different temporal scales: bacterial and archaeal richness peaks decades after retreat, whereas fungal richness peaks within a few years 7 . Our previous studies also highlighted the differentiation of fungal communities between glaciers and forelands. At Austre Brøggerbreen in Svalbard, yeasts such as Cryptococcus and Mrakia dominated on the glacier surface, whereas soil fungi including Mortierella and Cladosporium became prevalent in the foreland, with composition shifting along the retreat gradient 32 . Similarly, at Walker Glacier in the Canadian High Arctic, fungal isolates from glacier and foreland clustered separately, with only a small subset shared 33 . Other studies in polar and alpine environments also support the notion that microbial communities are independent of each other in glaciers and retreat areas 21 , 30 , 34 . Functional guild analysis revealed clear ecological differentiation in fungal trophic strategies along the glacier–foreland chronosequence. Glacier sites (Sites 1–3) were dominated by simple saprotrophs and algal-parasitic taxa, reflecting low organic matter availability and algal biomass as primary carbon sources on the ice surface. The presence of Chytrid Microfungi functioning as algal parasites or Pathotroph suggests reliance on transient or allochthonous organic substrates under oligotrophic conditions. In contrast, foreland sites (Sites 4–7) exhibited increasing representation of ectomycorrhizal, symbiotrophic, and ligninolytic taxa, including Corticioid and Microfungi associated with soil organic matter and plant-derived substrates. These changes correspond to the progressive development of soil and vegetation following deglaciation, as observed in other Arctic glacier forefields 27 , 33 – 34 . The dominance of Ectomycorrhizal and Pathotroph-Saprotroph guilds at Sites 6 and 7 indicates the establishment of mutualistic and decomposer-driven nutrient cycling during early pedogenesis. Overall, the observed transition from algal-parasitic and simple saprotrophic fungi on glacier ice to complex symbiotrophic and lignocellulolytic guilds in foreland soils reflects a fundamental ecological shift in energy acquisition and substrate utilization accompanying primary succession in polar terrestrial ecosystems. The ecological implications of these findings are wide-ranging. The independence of glacial microbial communities means that the ongoing retreat and eventual disappearance of glaciers under global warming will cause the loss of entire microbial assemblages. Microbes confined to glacier surfaces will lose their habitat completely, facing a high risk of extinction. Such losses will diminish microbial diversity locally, regionally, and globally, and may eliminate specialized taxa with unique traits and potential biogeochemical or biotechnological significance. Similar patterns have been observed in other polar and alpine glaciers globally, reinforcing the generality of these findings. Arklio Glacier’s terminus receded by 77m between 2001 and 2021 (Table 1 ), demonstrating the extreme speed of habitat loss of glacial habitats on Ellesmere Island. In conclusion, our study underscores the urgent need to recognize glaciers as reservoirs of microbial biodiversity. Preserving these fragile ecosystems is inseparable from efforts to mitigate climate change, and without action to slow warming, continued glacier loss will mean the irreversible disappearance of their hidden microbial life. Table 1 Sampling site coordinates and distance for the glacier terminus of Arklio Glacier Sampling Site latitute lognitude Distance from the glacier terminus (m) Location Additional notes Site 1 80.87679°N 82.83541°W -200 on the glacier Site 2 80.87542°N 82.83673°W -50 on the glacier Site 3 80.87579°N 82.84057°W 0 on the glacier Glacier terminus in 2022 Site 4 80.87472°N 82.83799°W 5 glacier retreat area Site 5 80.87455°N 82.83888°W 30 glacier retreat area Site 6 80.87393°N 82.83959°W 100 glacier retreat area Glacier terminus in 2002 Site 7 80.87078°N 82.83754°W 500 glacier retreat area Materials and Methods Sampling site Sediment samples were aseptically scraped from the surface of the melting ice face and terminal deposits of the Arklio Glacier (80°52′N, 82°49W) on Ellesmere Island in the Canadian High Arctic (Fig. 1 ), Nunavut, Canada, in July 2022, and transferred to sterile 5-mL tubes. Three sites were located on the glacial ice: Site 1 at 200 m from the glacier terminus, Site 2 at 50 from the glacier terminus and Site3 at the glacier terminus in 2022. An additional four sites were located on the exposed ground below the glacier. Sites 4 and site5 were 5 m and 30 m from the glacier terminus, respectively. Site 6 was located 100 m from the terminus of the glacier in an area that had been uncovered by the glacier retreat over the last 20 years. Site 7 was located approximately 500 m from the glacier terminus (Table 1 ). Within one hour after sampling, the samples were transferred to a -20°C freezer and stored at this temperature until analysis. DNA extraction and amplicon sequencing DNA was extracted from ~ 0.5 g soil samples using the FastDNA SPIN Kit for Soil (MP Biomedicals, CA, USA) according to the manufacturer’s instructions. DNA concentrations were measured with Qubit 4.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA). Bacterial and archaeal 16S rRNA gene was amplified using a universal primer set of 341F (5′-CCTACGGGNGGCWGCAG-3’) and 805R (5′-GACTACHVGGGTATCTAATCC-3’), targeting the V3–V4 region of the bacterial and archaea 16S rRNA gene 35 . The fungal internal transcribed spacer 1 (ITS1) region was amplified using the fungal universal primer sets ITS1F_KYO1 (5′- CTHGGTCATTTAGAGGAASTAA-3’) and ITS2_KYO2 (5′- TTYRCTRCGTTCTTCATC-3’) 36 . DNA was amplified with the following PCR protocol: an initial denaturation cycle (95°C for 3 min), 35 cycles of denaturation (95°C for 30 s), annealing (54°C for 30 s) and extension (72°C for 60 s), and a final extension cycle (72°C for 5 min). Triplicated reactions were conducted for each DNA sample and PCR products were verified by 1.5% agarose gel electrophoresis. Amplicons were purified using the Agencourt AMPure XP kit (Beckman Coulter, USA). Purified amplicons were paired-end sequenced on an Illumina MiSeq platform (Illumina, San Diego, CA) at a read length of 2 × 300 bp using the MiSeq reagent kit v3. For 16S rRNA, 803,995 reads were obtained from 7 samples (ranging from 86,874 to 152,056 reads per sample). In the ITS1 region, 684,805 reads were obtained from 7 samples (ranging from 55,855 to 145,548 per sample). After sequencing, the primary analysis of the raw FASTQ data was processed with the QIIME2 pipeline (version 2025.4) 37 . 16S rRNA analysis For 16S rRNA, DADA2 38 was used for error correction, quality filtering, chimera removal, and sequence variant calling of the Illumina amplicon sequences. The forward primer was truncated at 280 bp and the reverse primer at 210 bp, corresponding to a quality score of over 20. Finally, ASVs were clustered with dada2 with an identity threshold of 97%. Chimeras were removed, and ASVs were decontaminated with control reads. The Silva 138.2 database was used to assign taxonomy to ASVs with classify-sklearn classifier 39 . The ASVs that were taxonomically unclassified at phylum rank or were not assigned to bacterial lineage was excluded from further analysis. After quality control, 593,799 reads were retained from 803,995 raw reads. As a result, a total of 2,868 unique ASVs were generated from across seven samples. The phylogenetic rooted tree was generated using the MAFFT algorithm from within QIIME2 and was used for the diversity analysis. The ASV table was used for alpha diversity rarefaction analysis using an equal number of ASVs across samples (i.e. 10,000 sequences per sample). Beta diversity was measured by calculating unweighted UniFrac distances which consider the presence/absence of ASVs 40 across 7 samples and visualized through distance-based redundancy analysis (dbRDA) with relative abundance of bacteria followed by permutational multivariate analysis of variance (PERMANOVA) 41 . To quantify the extent of contribution of potential source to the sink, the Bayesian-based SourceTracker method was performed 42 . Predictive functional analysis of bacterial ASVs was performed using FAPROTAX 43 . ITS1 analysis The ITS1 region was extracted using ITSXpress. The extracted ITS1 regions underwent error correction, quality filtering, and chimera removal using DADA2, then were merged into OTUs using Vsearch. The UNITE 10.0 database was used to assign taxonomy to OTUs with classify-sklearn classifier 44 . The OTUs that were taxonomically unclassified at phylum rank or were not assigned to fungi lineage was excluded from further analysis. After quality control, 172,929 reads were retained from 684,805 raw reads. As a result, a total of 138 unique OTUs were generated from across seven samples. The phylogenetic rooted tree was generated using the MAFFT algorithm from within QIIME2 and was used for the diversity analysis. The OTU table was used for alpha diversity rarefaction analysis using an equal number of OTUs across samples (i.e. 10,000 sequences per sample). Beta diversity was measured by calculating unweighted UniFrac distances which consider the presence/absence of OTUs 40 across 7 samples and visualized through distance-based redundancy analysis (dbRDA) with relative abundance of bacteria followed by permutational multivariate analysis of variance (PERMANOVA) 41 . To quantify the extent of contribution of potential source to the sink, the Bayesian-based SourceTracker method was performed 42 . Functional analysis of OTUs was performed using FUNGuild 45 . Declarations Conflicts of interest None declared. Contributions Conceived and designed the experiments: MT, CG, WFV and MU. Performed the field sampling: WFV. Performed the laboratory experiments and analyses: MT. Analysed the data: MT. Wrote the manuscript: MT with input from all authors. Funding This work was supported by a JSPS Grant-in-Aid for Scientific Research (B) no. 23K28280 and the Arctic Challenge for Sustainability 3 (ArCS-3), Program Grant Number JPMXD1720251001. Additional support for the field work was provided by the Natural Sciences and Engineering Research Council of Canada, the ArcticNet/Sentinel North project NEIGE (Northern Ellesmere Island in the Global Environment), and the Polar Continental Shelf Program (PCSP). Author Contribution Conceived and designed the experiments: MT, CG, WFV and MU. Performed the field sampling: WFV. Performed the laboratory experiments and analyses: MT. Analysed the data: MT. Wrote the manuscript: MT with input from all authors. Acknowledgement We are grateful to Parks Canada and CEN for the use of facilities at Ellesmere Island in Quttinirpaaq National Park, Nunavut. The authors also thank K. Watanabe and M. Mori for technical assistance. 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The nitrogen cycle in cryoconites: naturally occurring nitrification–denitrification granules on a glacier. Environ. Microbiol. 16 , 3250–3262 (2014). Hattori, S., Li, Z., Yoshida, N. & Takeuchi, N. Isotopic evidence for microbial nitrogen cycling in a glacier interior of high-mountain Asia. Environ. Sci. Technol. 57 , 15026–15036 (2023). Tsuji, M., Uetake, J. & Tanabe, Y. Changes in the fungal community of Austre Brøggerbreen deglaciation area, Ny-Ålesund, Svalbard, High Arctic. Mycoscience 57 , 448–451 (2016). Tsuji, M., Vincent, W. F., Tanabe, Y. & Uchida, M. Glacier retreat results in loss of fungal diversity. Sustainability 14 , 1617 (2022). Peter, H. & Sommaruga, R. Shifts in diversity and function of lake bacterial communities upon glacier retreat. ISME J. 10 , 1545–1554 (2016). Herlemann, D. P. et al. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 5 , 1571–1579 (2011). Toju, H., Tanabe, A. S., Yamamoto, S. & Sato, H. High-coverage ITS primers for the DNA-based identification of ascomycetes and basidiomycetes in environmental samples. PLoS One . 7 , e40863 (2012). Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37 , 852–857 (2019). Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods . 13 , 581–583 (2016). Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41 , D590–D596 (2012). Lozupone, C., Lladser, M. E., Knights, D., Stombaugh, J. & Knight, R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 5 , 169–172 (2011). Anderson, M. J., Walsh, D. C. & PERMANOVA ANOSIM and the Mantel test in the face of heterogeneous dispersions: what null hypothesis are you testing? Ecol. Monogr. 83 , 557–574 (2013). Knights, D. et al. Bayesian community-wide culture-independent microbial source tracking. Nat. Methods . 8 , 761–763 (2011). Louca, S., Parfrey, L. W. & Doebeli, M. Decoupling function and taxonomy in the global ocean microbiome. Science 353 , 1272–1277 (2016). Nilsson, R. H. et al. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 47 , D259–D264. https://doi.org/10.1093/nar/gky1022 (2019). Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20 , 241–248 (2016). Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial2.xlsx Supplementarymaterial1.pptx Supplementarymaterial4.xlsx Supplementarymaterial3.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8090681","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":549440922,"identity":"bcd3a027-4fbc-4717-92e1-2d673d68be08","order_by":0,"name":"Masaharu Tsuji","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFACxgYGngIgLQHEH4CYjZ0oLQZADUAtjDNAWpiJsQimhZkHxCOkRX52c9uDNwY2dQa3m499tvm1TZ6PmYHxw8cc3FoM7hxsN5xjkCZhcOdY8uzcvtuGbcwMzJIzt+HRIpHYJs1jcFjC4EaOMXNuz21GoBY2Zl48WuRngLX8B2rJ/8xs2XPbnqAWhhtgLQdAtjAzM/y4nUhQC9AvbZJzDJIlZ945ZszY23A7uY2ZsRmvX+Rntz+TeFNhx893u/kxw48/t23ntzcf/PARn8MkkDmMbWCyAY96dC0Mf/ArHgWjYBSMgpEJAC9HThqJGr2sAAAAAElFTkSuQmCC","orcid":"","institution":"Nagaoka University of Technology","correspondingAuthor":true,"prefix":"","firstName":"Masaharu","middleName":"","lastName":"Tsuji","suffix":""},{"id":549440923,"identity":"0082e3b7-88d5-4a9a-8403-033a5a6d3180","order_by":1,"name":"Catherine Girard","email":"","orcid":"","institution":"Université Laval","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"","lastName":"Girard","suffix":""},{"id":549440924,"identity":"202aba11-ef74-4036-b194-e1d8f809bd3a","order_by":2,"name":"Warwick F. 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19:27:53","extension":"xml","order_by":17,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105353,"visible":true,"origin":"","legend":"","description":"","filename":"6caf1852872d44e8847b3e82fe53b6c21structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/8b37d7105cb21d7327882d20.xml"},{"id":96915978,"identity":"99052412-4ac0-4092-88e0-c40e06b5bf0d","added_by":"auto","created_at":"2025-11-27 14:07:50","extension":"html","order_by":18,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":117124,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/8e9b80d8cd2383b970932157.html"},{"id":96761526,"identity":"0197991e-5dc6-49a5-9f74-bc0399f9bfbb","added_by":"auto","created_at":"2025-11-25 19:27:53","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":210971,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLocation map of Ellesmere Island and sampling sites\u003c/strong\u003e \u003cstrong\u003ein the Canadian High Arctic.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) Location of the Arklio Glacier in Ellesmere Island, (B) Sampling sites on the Arklio Glacier\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/03bee89a982d8bfc79f5d4c7.jpeg"},{"id":96915805,"identity":"757fb0a7-c534-40be-a92e-67a9633b2e23","added_by":"auto","created_at":"2025-11-27 14:07:39","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":215150,"visible":true,"origin":"","legend":"\u003cp\u003ePhylum-level relative abundance on Arklio glacier area based on 16S rRNA gene sequencing\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/8536b78f56b22e3c9a853bc6.jpeg"},{"id":96761530,"identity":"9eb33404-e7b8-4850-b4ff-1484d3c3a3e5","added_by":"auto","created_at":"2025-11-25 19:27:53","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":245011,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBacterial community structure revealed by 16S rRNA gene analysis. \u0026nbsp;\u003c/strong\u003e(A) Heatmap analysis. The red frame in the figure indicates on the glacier, while the black frame indicates the glacier retreat area. (B) PERMANOVA analysis. The graph shows the glacier area on the left and the glacier retreat area on the right. The bottom of the graph displays the results of the PERMANOVA analysis. (C) Source tracking analysis of glacier retreating area. The vertical axis represents the percentage of bacteria originating from the glacial retreat areas among the sources in the glacial retreat areas (orange). Second vertical axes indicate the percentage of bacteria originating from the glacial areas among the sources on the glacier retreat area (blue). Note the different scales in each axis. (D) Source tracking analysis on the glacier. The vertical axis represents the percentage of bacteria originating from on the glacial areas among the sources in the glacial areas (orange). Second vertical axes indicate the percentage of bacteria originating from the glacial retreat areas among the sources on the glacier area (green). Note the different scales in each axis. (E) Relationship between Shannon diversity of bacterial communities on the glacier and in glacial retreating area, and distance from the glacier terminus. Blue circles indicate areas on the glacier, while orange diamonds represent areas of glacial retreat area.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/d098c0ee9ec2ec613c7288cf.jpeg"},{"id":96761532,"identity":"9ec38e38-5b9a-43d4-8136-03d180a12192","added_by":"auto","created_at":"2025-11-25 19:27:53","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180617,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePhylum-level relative abundance on Arklio glacier area based on ITS1 region sequencing\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/f7705e2307b15acb19ec9229.jpeg"},{"id":96761544,"identity":"1dc09363-cbfa-4a19-a3a0-1e43ca2e7925","added_by":"auto","created_at":"2025-11-25 19:27:53","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":253219,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFungal community structure revealed by ITS region analysis. \u0026nbsp;\u003c/strong\u003e(A) Heatmap analysis. The red frame in the figure indicates on the glacier, while the black frame indicates the glacier retreat area. (B) PERMANOVA analysis. The graph shows the glacier area on the left and the glacier retreat area on the right. The bottom of the graph displays the results of the PERMANOVA analysis. (C) Source tracking analysis of glacier retreating area. The vertical axis represents the percentage of fungi originating from the glacial retreat areas among the sources in the glacial retreat areas (orange). Second vertical axes indicate the percentage of fungi originating from the glacial areas among the sources on the glacier retreat area (blue). Note the different scales in each axis. (D) Source tracking analysis on the glacier. The vertical axis represents the percentage of fungi originating from on the glacial areas among the sources in the glacial areas (orange). Second vertical axes indicate the percentage of fungi originating from the glacial retreat areas among the sources on the glacier area (green). Note the different scales in each axis. (E) Relationship between Shannon diversity of fungi communities on the glacier and in glacial retreating area, and distance from the glacier terminus. Blue circles indicate areas on the glacier, while orange diamonds represent areas of glacial retreat area.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/55e63071265992429de44018.jpeg"},{"id":100025017,"identity":"82fe53f9-3421-43ed-927f-040ba6b796e7","added_by":"auto","created_at":"2026-01-12 08:25:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1946052,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/98bcef31-17a4-4c43-93c0-46ef7661624a.pdf"},{"id":96915261,"identity":"ffc9628c-33ab-4a87-97d5-d94417a70fc9","added_by":"auto","created_at":"2025-11-27 14:07:02","extension":"xlsx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":10990,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/636389f34d2f48a0c399867f.xlsx"},{"id":96761549,"identity":"c454f236-de37-4b6b-aa13-1d397c911d04","added_by":"auto","created_at":"2025-11-25 19:27:53","extension":"pptx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3768613,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial1.pptx","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/dfb52b7b0db635e54853cdc1.pptx"},{"id":96916103,"identity":"5cdf4f64-410b-4d1d-8a54-96881c6f4d4b","added_by":"auto","created_at":"2025-11-27 14:08:01","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":29916,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/284120a658eb6f88c376ddf5.xlsx"},{"id":96761542,"identity":"3a0338b2-adc5-4f94-9894-f5e582cfb149","added_by":"auto","created_at":"2025-11-25 19:27:53","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":13415,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-8090681/v1/9697826eb338bc990782db88.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Glacier retreat threatens unique microbial communities and biogeochemical functions confined to glacier surfaces","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGlaciers cover nearly 10% of Earth\u0026rsquo;s land surface\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e and play a crucial role in regulating global climate and hydrological cycles. However, they are strongly affected by environmental change and, in recent decades, have experienced major reductions in area, particularly in the High Arctic\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. This loss not only reduces ice mass but also threatens unique microbial habitats in the cryosphere, even in slow-changing systems\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Beyond their physical and climatic importance, glaciers also harbor diverse microbial communities that sustain primary production and nutrient turnover in extreme oligotrophic environments\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. These microbial assemblages form self-sufficient ecosystems within cryoconite holes, ice surfaces, and subglacial niches, where they mediate essential biogeochemical processes such as carbon fixation and nutrient regeneration\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. However, accelerated glacier retreat under climate warming is transforming these ecosystems at an unprecedented rate, leading to the potential loss of unique microbial habitats and their associated functions\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003ePrevious studies in Arctic, Antarctic, and alpine regions have demonstrated strong ecological differentiation between microbial communities inhabiting glacier ice and those in deglaciated forelands\u003csup\u003e\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, where newly exposed sediments progressively develop into soils colonized by plants and heterotrophic microbes. On glacier surfaces, phototrophic bacteria and algae dominate, fueling primary production through oxygenic photoautotrophy under intense solar radiation and nutrient limitation\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. In contrast, foreland communities are typically enriched in heterotrophic and nitrifying taxa that utilize organic matter accumulating with soil formation and vegetation establishment\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This transition from autotrophic to heterotrophic energy pathways represents a fundamental reorganization of carbon and nitrogen cycling following glacier retreat\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Yet, the functional divergence between these two coupled ecosystems \u0026ndash; and its implications for biogeochemical feedback \u0026ndash; remains poorly quantified, and little attention has been given to micro-fungi, despite their unique functional roles in cryospheric habitats.\u003c/p\u003e\u003cp\u003eThe Arklio Glacier (80\u0026deg;50\u0026prime;N, 82\u0026deg;50\u0026prime;W) on Ellesmere Island in the Canadian High Arctic, provides an ideal setting to examine this ecological and functional transition. The glacier and its foreland represent a chronosequence of deglaciation, with well-preserved moraines that record successive retreat stages since the Last Glacial Maximum. Although geomorphological and botanical features of this foreland have been characterized, microbial diversity and function remain unexplored. Here, we conducted a comprehensive analysis of bacterial and fungal communities across seven sites spanning the glacier surface and foreland. Using high-throughput amplicon sequencing, SourceTracker, and functional prediction approaches (FAPROTAX and FUNGuild), we aimed to (i) characterize microbial diversity and community composition, (ii) identify habitat-specific functional traits, and (iii) assess how these communities shift across glacier and foreland environments at the Arklio Glacier and its foreland in the Canadian High Arctic.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eBacterial and archaeal abundances and their diversity patterns\u003c/h2\u003e\u003cp\u003eThe results of the taxonomic composition of 16S rRNA sequences were as follows: At Sites 1\u0026ndash;3, Proteobacteria, Cyanobacteriota, Bacteroidota, and Chloroflexi together accounted for more than 70% of the total relative frequency of 16S rRNA gene sequences. At Site 4, Proteobacteria, Bacteroidota, and Chloroflexi were dominant, representing over 70% of the community. At Site 5, Actinobacteriota appeared in addition to Proteobacteria, Cyanobacteriota, Bacteroidota, and Chloroflexi, collectively exceeding 70% of the total relative frequency. At foreland Sites 6 and 7, the relative abundance of Acidobacteriota increased alongside Proteobacteria, Cyanobacteriota, Bacteroidota, Chloroflexi, and Actinobacteriota (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). For Archaea, the phylum Halobacterota accounted for approximately 0.005% of the relative abundance at Site 3, while Crenarchaeota accounted for about 0.03% at Site 7.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of heatmap data from 16S rRNA sequences indicated that Sites 1\u0026ndash;3 displayed largely comparable community profiles; however, Site 3 demonstrated a relatively elevated abundance of Firmicutes in comparison to the other glacier sites (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In contrast, Sites 4\u0026ndash;7 in the foreland showed broadly similar overall patterns but with site-specific compositional features. At Site 4, Campylobacterota and Hydrogenedentes displayed notably higher relative abundances. At Site 6, Fibrobacterota and Nitrospirota were relatively enriched, whereas at Site 7, Sumeriaeota showed a relatively abundance increase while Deinococcota was lower relative abundance compared to Sites 4\u0026ndash;6. Site 5 did not exhibit distinct relative abundance features (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The results of the PERMANOVA analysis indicates that there were significant differences in community structure among sites (F\u0026thinsp;=\u0026thinsp;2.685619, p\u0026thinsp;=\u0026thinsp;0.023; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBased on the SourceTracker analysis of 16S rRNA sequences, ASVs originating from Sites 1\u0026ndash;3 (on-glacier) accounted for less than 3.5% of the total sequences detected in Sites 4\u0026ndash;7 (foreland). Conversely, ASVs from foreland sites contributed only about 1.5% to the on-glacier communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D).\u003c/p\u003e\u003cp\u003eAlpha diversity indices are summarized in Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e. Among the four indices, Shannon, Faith\u0026rsquo;s phylogenetic diversity (PD), and Observed Features were lowest at Site 4, located immediately beyond the glacier terminus (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eE, Fig.\u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). In contrast, Evenness values remained high (\u0026gt;\u0026thinsp;0.7) and relatively constant across all sites.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eFungal abundances and their diversity patterns\u003c/h3\u003e\n\u003cp\u003eThe results of the taxonomic composition of fungal communities based on ITS sequences were as follows. At Sites 1\u0026ndash;3 (on-glacier sites), Ascomycota, Fungi_phyla_Incertae_sedis and Chytridiomycota were predominant, together accounting for over 70% of the total relative abundance. At Site 4 (at the glacier terminus), Basidiomycota and Ascomycota were dominant, with minor contributions from Mucoromycota and Aphelidiomycota. At Site 5, Ascomycota and Basidiomycota, collectively comprised more than 70% of the community. At Sites 6 and 7, Ascomycota, Basidiomycota, and Fungi phy. Incertae sedis remained dominant. Sanchytriomycota was detected at Sites 1, 2, and 7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eHeatmap visualization of ITS1 region diversity revealed broadly comparable community profiles at Sites 1\u0026ndash;3 on the glacier, with notable site-specific variations. Notably, Sordariomycetes exhibited a relatively high frequency at Site 1. Conversely, Dothideomycetes demonstrated comparatively lower abundance at Site 2. In contrast, Sites 3 showcased a significant abundance of Ascomycota, Orbiliomycetes, and Eurotiomycetes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Sites 4\u0026ndash;7 in the foreland also shared overall similar patterns, though each site displayed distinct taxonomic characteristics. At Site 4, Sordariomycetes and Agaricomycetes were abundant; Site 5 was dominated by Agaricomycetes; and Sites 6 and 7 showed relatively higher abundances of Ascomycota (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). The results of the PERMANOVA analysis indicates that there were significant differences in community structure among sites (F\u0026thinsp;=\u0026thinsp;2.88891, p\u0026thinsp;=\u0026thinsp;0.036; Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn the SourceTracker analysis of fungal ITS1 region sequences, OTUs originating from Sites 1 and 3 accounted for less than 1.5% of the total sequences detected in Sites 4\u0026ndash;7, while those from Site 2 contributed approximately 4%. Conversely, OTUs from foreland sites (Sites 4\u0026ndash;7) were detected at low frequencies in on-glacier communities: less than 1.6% in Sites 5 and 7, around 2.5% in Site 4, and approximately 3.6% in Site 6 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eC-D).\u003c/p\u003e\u003cp\u003eFungal alpha diversity indices are summarized in Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e. Site 3 exhibited the lowest values for Shannon, Faith\u0026rsquo;s phylogenetic diversity (PD), and Observed Features, indicating reduced fungal richness and phylogenetic diversity at this location. However, the Evenness index remained above 0.6 across all sites, with Sites 3 and 5 showing the highest values (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, Fig.\u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eFunctional prediction of bacterial, archaea and fungal communities\u003c/h3\u003e\n\u003cp\u003eIn the functional prediction of bacterial and archaea communities by FAPROTAX, the top five predicted functions accounted for more than 70% of the total ASV counts across Sites 1\u0026ndash;7 in each site. At Sites 1\u0026ndash;3, the top five functions were identical and consisted of phototrophy, photoautotrophy, cyanobacteria, oxygenic photoautotrophy, and chemoheterotrophy. At Sites 4\u0026ndash;7, chemoheterotrophy and aerobic chemoheterotrophy alone represented approximately 60% or more of the total ASV counts in each site. Chemoheterotrophy appeared consistently among the top five predicted functions at all sites (Table \u003cspan refid=\"MOESM3\" class=\"InternalRef\"\u003eS3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFor fungal communities, the top five OTUs at each site accounted for more than 60% of the total OTU abundance. Functional guild prediction using FUNGuild showed that a large number of OTUs taxonomically classified as Fungi or Fungi_phy_Incertae_sedis could not be functionally annotated. Among the functionally assigned OTUs, the dominant guilds varied by site. At Site 1, Saprotroph and Pathotroph were dominant; at Site 2, Saprotroph and Saprotroph-Symbiotroph were most abundant. Site 3 was characterized by Lichenized Microfungi (Symbiotroph) and Chytrid Microfungi (Algal Parasite). At Site 4, Microfungi classified as Saprotroph and Chytrid Microfungi as Pathotroph-Saprotroph predominated. At Site 5, Corticioid Fungi (Algal Parasite) and Microfungi (Saprotroph) were prevalent, while at Site 6, Corticioid Fungi (Ectomycorrhizal) and Microfungi (Pathotroph-Saprotroph) dominated. Finally, Site 7 was characterized by Microfungi (Saprotroph) and Corticioid Microfungi (Ectomycorrhizal) (Table \u003cspan refid=\"MOESM4\" class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eResults of 16S rRNA sequencing analyzed through taxonomy, heatmaps and PERMANOVA revealed significant differences between on-glacier and foreland bacterial and archaea assemblages (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eA-B), and SourceTracker analysis further indicated that the two communities were largely independent with minimal overlap (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eC-D). On the glacier, Shannon, Faith PD, and Observed Feature indices increased toward the terminus, suggesting gradual enrichment of microbial diversity. In the foreland, these indices initially decreased just beyond the terminus but peaked at ~\u0026thinsp;100 m, corresponding to ca. 20 years after glacier retreat, before stabilizing. Evenness remained stable (\u0026gt;\u0026thinsp;0.7) across habitats (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003eE; Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). These results demonstrate that dispersal between glacier and foreland habitats is limited, with each sustaining unique communities shaped by contrasting environmental conditions and hydrological isolation\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFunctional predictions of bacteria and archaea revealed habitat-specific metabolic potentials. On the glacier, phototrophic-associated indicators such as cyanobacteria and oxygenic photoautotrophy dominated, suggesting that primary production is maintained by light-dependent processes under nutrient-poor, high-radiation conditions\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. In contrast, ASV detection in the foreland was dominated by two functions: chemoheterotrophy and aerobic chemoheterotrophy. This pattern reflects a metabolic shift toward heterotrophic energy acquisition following the accumulation of organic matter after glacier retreat\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Moreover, nitrification-related functions, including aerobic ammonia and nitrite oxidation, were detected at low frequencies and mainly in foreland soils, suggesting the onset of nitrogen cycling during early soil development\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNevertheless, trace signals of nitrogen fixation and nitrate reduction were also detected in glacier surface samples, indicating that limited nitrogen transformations may occur even under oligotrophic ice conditions.\u003c/p\u003e\u003cp\u003ePrevious studies have reported that such processes can vary considerably among glacier systems \u0026ndash; for example, nitrification and denitrification in cryoconite granules (Segawa et al., 2014) and isotopic evidence of nitrogen cycling within glacier interiors (Hattori et al., 2023) \u0026ndash; highlighting that while the Arklio Glacier system shows restricted nitrogen activity on ice, it follows the broader pattern of functional differentiation between glaciers and their forelands.\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eConsistent with bacterial and archaea assemblages, fungal communities exhibited a similar independence but a contrasting diversity trajectory (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA-B). PERMANOVA and SourceTracker analyses confirmed clear separation between glacier and foreland assemblages (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA\u0026ndash;D). On the glacier, Shannon, Faith PD, and Observed Feature indices decreased toward the terminus, while in the foreland, diversity peaked around 30 m from the terminus before stabilizing. Evenness remained above 0.6 in both environments, suggesting stable species distribution (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eE; Fig. \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese patterns suggest that bacterial, archaeal and fungal communities respond to deglaciation on different temporal scales: bacterial and archaeal richness peaks decades after retreat, whereas fungal richness peaks within a few years\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eOur previous studies also highlighted the differentiation of fungal communities between glaciers and forelands. At Austre Br\u0026oslash;ggerbreen in Svalbard, yeasts such as \u003cem\u003eCryptococcus\u003c/em\u003e and \u003cem\u003eMrakia\u003c/em\u003e dominated on the glacier surface, whereas soil fungi including \u003cem\u003eMortierella\u003c/em\u003e and \u003cem\u003eCladosporium\u003c/em\u003e became prevalent in the foreland, with composition shifting along the retreat gradient\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Similarly, at Walker Glacier in the Canadian High Arctic, fungal isolates from glacier and foreland clustered separately, with only a small subset shared\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Other studies in polar and alpine environments also support the notion that microbial communities are independent of each other in glaciers and retreat areas\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFunctional guild analysis revealed clear ecological differentiation in fungal trophic strategies along the glacier\u0026ndash;foreland chronosequence. Glacier sites (Sites 1\u0026ndash;3) were dominated by simple saprotrophs and algal-parasitic taxa, reflecting low organic matter availability and algal biomass as primary carbon sources on the ice surface. The presence of Chytrid Microfungi functioning as algal parasites or Pathotroph suggests reliance on transient or allochthonous organic substrates under oligotrophic conditions. In contrast, foreland sites (Sites 4\u0026ndash;7) exhibited increasing representation of ectomycorrhizal, symbiotrophic, and ligninolytic taxa, including Corticioid and Microfungi associated with soil organic matter and plant-derived substrates. These changes correspond to the progressive development of soil and vegetation following deglaciation, as observed in other Arctic glacier forefields \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. The dominance of Ectomycorrhizal and Pathotroph-Saprotroph guilds at Sites 6 and 7 indicates the establishment of mutualistic and decomposer-driven nutrient cycling during early pedogenesis. Overall, the observed transition from algal-parasitic and simple saprotrophic fungi on glacier ice to complex symbiotrophic and lignocellulolytic guilds in foreland soils reflects a fundamental ecological shift in energy acquisition and substrate utilization accompanying primary succession in polar terrestrial ecosystems.\u003c/p\u003e\u003cp\u003eThe ecological implications of these findings are wide-ranging. The independence of glacial microbial communities means that the ongoing retreat and eventual disappearance of glaciers under global warming will cause the loss of entire microbial assemblages. Microbes confined to glacier surfaces will lose their habitat completely, facing a high risk of extinction. Such losses will diminish microbial diversity locally, regionally, and globally, and may eliminate specialized taxa with unique traits and potential biogeochemical or biotechnological significance. Similar patterns have been observed in other polar and alpine glaciers globally, reinforcing the generality of these findings. Arklio Glacier\u0026rsquo;s terminus receded by 77m between 2001 and 2021 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), demonstrating the extreme speed of habitat loss of glacial habitats on Ellesmere Island. In conclusion, our study underscores the urgent need to recognize glaciers as reservoirs of microbial biodiversity. Preserving these fragile ecosystems is inseparable from efforts to mitigate climate change, and without action to slow warming, continued glacier loss will mean the irreversible disappearance of their hidden microbial life.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSampling site coordinates and distance for the glacier terminus of Arklio Glacier\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSampling Site\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003elatitute\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003elognitude\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDistance from the glacier terminus (m)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLocation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eAdditional notes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87679\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.83541\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eon the glacier\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87542\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.83673\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eon the glacier\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87579\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.84057\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eon the glacier\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGlacier terminus in 2022\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87472\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.83799\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eglacier retreat area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87455\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.83888\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eglacier retreat area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87393\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.83959\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eglacier retreat area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eGlacier terminus in 2002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSite 7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e80.87078\u0026deg;N\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82.83754\u0026deg;W\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eglacier retreat area\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eSampling site\u003c/h2\u003e\u003cp\u003eSediment samples were aseptically scraped from the surface of the melting ice face and terminal deposits of the Arklio Glacier (80\u0026deg;52\u0026prime;N, 82\u0026deg;49W) on Ellesmere Island in the Canadian High Arctic (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e), Nunavut, Canada, in July 2022, and transferred to sterile 5-mL tubes. Three sites were located on the glacial ice: Site 1 at 200 m from the glacier terminus, Site 2 at 50 from the glacier terminus and Site3 at the glacier terminus in 2022. An additional four sites were located on the exposed ground below the glacier. Sites 4 and site5 were 5 m and 30 m from the glacier terminus, respectively. Site 6 was located 100 m from the terminus of the glacier in an area that had been uncovered by the glacier retreat over the last 20 years. Site 7 was located approximately 500 m from the glacier terminus (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Within one hour after sampling, the samples were transferred to a -20\u0026deg;C freezer and stored at this temperature until analysis.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eDNA extraction and amplicon sequencing\u003c/h3\u003e\n\u003cp\u003eDNA was extracted from ~\u0026thinsp;0.5 g soil samples using the FastDNA SPIN Kit for Soil (MP Biomedicals, CA, USA) according to the manufacturer\u0026rsquo;s instructions. DNA concentrations were measured with Qubit 4.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA).\u003c/p\u003e\u003cp\u003eBacterial and archaeal 16S rRNA gene was amplified using a universal primer set of 341F (5\u0026prime;-CCTACGGGNGGCWGCAG-3\u0026rsquo;) and 805R (5\u0026prime;-GACTACHVGGGTATCTAATCC-3\u0026rsquo;), targeting the V3\u0026ndash;V4 region of the bacterial and archaea 16S rRNA gene\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. The fungal internal transcribed spacer 1 (ITS1) region was amplified using the fungal universal primer sets ITS1F_KYO1 (5\u0026prime;- CTHGGTCATTTAGAGGAASTAA-3\u0026rsquo;) and ITS2_KYO2 (5\u0026prime;- TTYRCTRCGTTCTTCATC-3\u0026rsquo;)\u003csup\u003e36\u003c/sup\u003e. DNA was amplified with the following PCR protocol: an initial denaturation cycle (95\u0026deg;C for 3 min), 35 cycles of denaturation (95\u0026deg;C for 30 s), annealing (54\u0026deg;C for 30 s) and extension (72\u0026deg;C for 60 s), and a final extension cycle (72\u0026deg;C for 5 min). Triplicated reactions were conducted for each DNA sample and PCR products were verified by 1.5% agarose gel electrophoresis. Amplicons were purified using the Agencourt AMPure XP kit (Beckman Coulter, USA). Purified amplicons were paired-end sequenced on an Illumina MiSeq platform (Illumina, San Diego, CA) at a read length of 2 \u0026times; 300 bp using the MiSeq reagent kit v3. For 16S rRNA, 803,995 reads were obtained from 7 samples (ranging from 86,874 to 152,056 reads per sample). In the ITS1 region, 684,805 reads were obtained from 7 samples (ranging from 55,855 to 145,548 per sample). After sequencing, the primary analysis of the raw FASTQ data was processed with the QIIME2 pipeline (version 2025.4)\u003csup\u003e37\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003e16S rRNA analysis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor 16S rRNA, DADA2\u003csup\u003e38\u003c/sup\u003e was used for error correction, quality filtering, chimera removal, and sequence variant calling of the Illumina amplicon sequences. The forward primer was truncated at 280 bp and the reverse primer at 210 bp, corresponding to a quality score of over 20. Finally, ASVs were clustered with dada2 with an identity threshold of 97%. Chimeras were removed, and ASVs were decontaminated with control reads. The Silva 138.2 database was used to assign taxonomy to ASVs with classify-sklearn classifier\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. The ASVs that were taxonomically unclassified at phylum rank or were not assigned to bacterial lineage was excluded from further analysis. After quality control, 593,799 reads were retained from 803,995 raw reads. As a result, a total of 2,868 unique ASVs were generated from across seven samples. The phylogenetic rooted tree was generated using the MAFFT algorithm from within QIIME2 and was used for the diversity analysis. The ASV table was used for alpha diversity rarefaction analysis using an equal number of ASVs across samples (i.e. 10,000 sequences per sample). Beta diversity was measured by calculating unweighted UniFrac distances which consider the presence/absence of ASVs\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e across 7 samples and visualized through distance-based redundancy analysis (dbRDA) with relative abundance of bacteria followed by permutational multivariate analysis of variance (PERMANOVA)\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. To quantify the extent of contribution of potential source to the sink, the Bayesian-based SourceTracker method was performed\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Predictive functional analysis of bacterial ASVs was performed using FAPROTAX\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eITS1 analysis\u003c/h3\u003e\n\u003cp\u003eThe ITS1 region was extracted using ITSXpress. The extracted ITS1 regions underwent error correction, quality filtering, and chimera removal using DADA2, then were merged into OTUs using Vsearch. The UNITE 10.0 database was used to assign taxonomy to OTUs with classify-sklearn classifier\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. The OTUs that were taxonomically unclassified at phylum rank or were not assigned to fungi lineage was excluded from further analysis. After quality control, 172,929 reads were retained from 684,805 raw reads. As a result, a total of 138 unique OTUs were generated from across seven samples. The phylogenetic rooted tree was generated using the MAFFT algorithm from within QIIME2 and was used for the diversity analysis. The OTU table was used for alpha diversity rarefaction analysis using an equal number of OTUs across samples (i.e. 10,000 sequences per sample). Beta diversity was measured by calculating unweighted UniFrac distances which consider the presence/absence of OTUs\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e across 7 samples and visualized through distance-based redundancy analysis (dbRDA) with relative abundance of bacteria followed by permutational multivariate analysis of variance (PERMANOVA)\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. To quantify the extent of contribution of potential source to the sink, the Bayesian-based SourceTracker method was performed\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Functional analysis of OTUs was performed using FUNGuild\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflicts of interest\u003c/h2\u003e\u003cp\u003eNone declared.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eContributions\u003c/h2\u003e\u003cp\u003eConceived and designed the experiments: MT, CG, WFV and MU. Performed the field sampling: WFV. Performed the laboratory experiments and analyses: MT. Analysed the data: MT. Wrote the manuscript: MT with input from all authors.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis work was supported by a JSPS Grant-in-Aid for Scientific Research (B) no. 23K28280 and the Arctic Challenge for Sustainability 3 (ArCS-3), Program Grant Number JPMXD1720251001. Additional support for the field work was provided by the Natural Sciences and Engineering Research Council of Canada, the ArcticNet/Sentinel North project NEIGE (Northern Ellesmere Island in the Global Environment), and the Polar Continental Shelf Program (PCSP).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceived and designed the experiments: MT, CG, WFV and MU. Performed the field sampling: WFV. Performed the laboratory experiments and analyses: MT. Analysed the data: MT. Wrote the manuscript: MT with input from all authors.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe are grateful to Parks Canada and CEN for the use of facilities at Ellesmere Island in Quttinirpaaq National Park, Nunavut. The authors also thank K. Watanabe and M. Mori for technical assistance.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAmplicons in this study are under the Bioproject PRJDB37681 for 16S rRNA and PRJDB37682 for ITS1.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCauvy-Frauni\u0026eacute;, S. \u0026amp; Dangles, O. A global synthesis of biodiversity responses to glacier retreat. \u003cem\u003eNat. Ecol. 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FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. \u003cem\u003eFungal Ecol.\u003c/em\u003e \u003cb\u003e20\u003c/b\u003e, 241\u0026ndash;248 (2016).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"High Arctic, glacier retreat, microbial community, climate change, 16S rRNA, ITS1 region","lastPublishedDoi":"10.21203/rs.3.rs-8090681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8090681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eGlaciers are rapidly retreating under climate warming, with potential loss of unique microbial ecosystems. Here, we investigated bacterial and fungal communities across the glacier surface and foreland of the Arklio Glacier, Canadian High Arctic, using 16S and ITS amplicon sequencing. Both bacterial and fungal communities on the glacier were distinct and largely independent from those in the foreland, indicating limited microbial dispersal and strong environmental filtering. Alpha diversity patterns revealed opposite trends between the two groups: bacterial diversity increased toward the glacier terminus, whereas fungal diversity declined. In the foreland, bacterial diversity peaked around 100 m (~\u0026thinsp;20 years post-retreat), while fungal diversity reached a maximum at 20 m, suggesting distinct successional responses to deglaciation. Functional predictions indicated contrasting metabolic strategies: phototrophy dominated on glacier ice, whereas chemoheterotrophy and nitrification prevailed in foreland soils. Together, these results demonstrate that glacier retreat reshapes both microbial composition and function, and underscore how glaciers are threatened reservoirs of microbial biodiversity.\u003c/p\u003e","manuscriptTitle":"Glacier retreat threatens unique microbial communities and biogeochemical functions confined to glacier surfaces","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-25 19:27:48","doi":"10.21203/rs.3.rs-8090681/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"0300ba14-2865-42af-a7fb-e4881397c7fa","owner":[],"postedDate":"November 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58460309,"name":"Biological sciences/Ecology"},{"id":58460310,"name":"Earth and environmental sciences/Ecology"},{"id":58460311,"name":"Earth and environmental sciences/Environmental sciences"},{"id":58460312,"name":"Biological sciences/Microbiology"}],"tags":[],"updatedAt":"2026-01-12T08:23:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-25 19:27:48","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8090681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8090681","identity":"rs-8090681","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}