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  <front>
    <journal-meta><journal-id journal-id-type="publisher">TC</journal-id><journal-title-group>
    <journal-title>The Cryosphere</journal-title>
    <abbrev-journal-title abbrev-type="publisher">TC</abbrev-journal-title><abbrev-journal-title abbrev-type="nlm-ta">The Cryosphere</abbrev-journal-title>
  </journal-title-group><issn pub-type="epub">1994-0424</issn><publisher>
    <publisher-name>Copernicus Publications</publisher-name>
    <publisher-loc>Göttingen, Germany</publisher-loc>
  </publisher></journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.5194/tc-20-4957-2026</article-id><title-group><article-title>Distinct phototrophic community structure on a Central Asian glacier: predominance of filamentous cyanobacteria and absence of glacier algae (<italic>Ancylonema</italic> spp.)</article-title><alt-title>Distinct phototrophic community structure on a Central Asian glacier</alt-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" corresp="no" rid="aff1 aff2">
          <name><surname>Chen</surname><given-names>Yunjie</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="yes" rid="aff3">
          <name><surname>Takeuchi</surname><given-names>Nozomu</given-names></name>
          <email>ntakeuch@faculty.chiba-u.jp</email>
        <ext-link>https://orcid.org/0000-0002-3267-5534</ext-link></contrib>
        <contrib contrib-type="author" corresp="no" rid="aff4">
          <name><surname>Tanaka</surname><given-names>Sota</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Li</surname><given-names>Saifei</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff1">
          <name><surname>Zhang</surname><given-names>Weizhen</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff5">
          <name><surname>Huang</surname><given-names>Xingyu</given-names></name>
          
        </contrib>
        <contrib contrib-type="author" corresp="no" rid="aff6">
          <name><surname>Li</surname><given-names>Zhongqin</given-names></name>
          
        </contrib>
        <aff id="aff1"><label>1</label><institution>Center for Pan-Third Pole Environment, Lanzhou University, Lanzhou, China</institution>
        </aff>
        <aff id="aff2"><label>2</label><institution>Chayu Integrated Observation and Research Station of the Xizang Autonomous Region, Xizang, China</institution>
        </aff>
        <aff id="aff3"><label>3</label><institution>Center for Environmental Remote Sensing, Chiba University, Chiba, Japan</institution>
        </aff>
        <aff id="aff4"><label>4</label><institution>Graduate School of Science, Chiba University, Chiba, Japan</institution>
        </aff>
        <aff id="aff5"><label>5</label><institution>Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China</institution>
        </aff>
        <aff id="aff6"><label>6</label><institution>State Key Laboratory of Cryospheric Sciences/Tien Shan Glaciological Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">Nozomu Takeuchi (ntakeuch@faculty.chiba-u.jp)</corresp></author-notes><pub-date><day>3</day><month>September</month><year>2026</year></pub-date>
      
      <volume>20</volume>
      <issue>9</issue>
      <fpage>4957</fpage><lpage>4972</lpage>
      <history>
        <date date-type="received"><day>8</day><month>March</month><year>2026</year></date>
           <date date-type="rev-request"><day>20</day><month>March</month><year>2026</year></date>
           <date date-type="rev-recd"><day>8</day><month>August</month><year>2026</year></date>
           <date date-type="accepted"><day>24</day><month>August</month><year>2026</year></date>
      </history>
      <permissions>
        <copyright-statement>Copyright: © 2026 Yunjie Chen et al.</copyright-statement>
        <copyright-year>2026</copyright-year>
      <license license-type="open-access"><license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p></license></permissions><self-uri xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026.html">This article is available from https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026.html</self-uri><self-uri xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026.pdf">The full text article is available as a PDF file from https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026.pdf</self-uri>
      <abstract><title>Abstract</title>

      <p id="d2e174">Cold-adapted algae and cyanobacteria are key drivers of snow and ice albedo reduction, yet their dynamics on dust-rich Central Asian glaciers remain poorly understood compared to the well-documented algal blooms in the Arctic. This study investigated the spatio-temporal distribution of phototrophic communities on Urumqi Glacier No. 1, eastern Tien Shan, during a two-month melt season. Our findings reveal a distinct seasonal succession where snow-covered surfaces were dominated by snow algae <italic>Chloromonadinia</italic> species, whereas the ablation of snow exposed the bare-ice surface, manifesting as a sharp biomass increase dominated by the newly uncovered filamentous cyanobacteria (Oscillatoriaceae). Notably, glacier algae such as <italic>Ancylonema</italic> spp., which drive darkening on Arctic ice, were entirely absent, suggesting a fundamental ecological divergence. Statistical analyses indicated that cyanobacterial proliferation is closely linked to environmental factors, showing significant positive correlations with mineral-derived ions and negative correlations with inorganic nitrogen. These results, supported by recent evidence that specialized cyanobacterial taxa drive the initiation and structural development of cryoconite granules, suggest that mineral-rich glacier surfaces may provide environmental conditions favorable for the persistence of cyanobacteria-dominated communities. The widespread coverage of bare ice surfaces by dispersed cryoconite composed of filamentous cyanobacteria and mineral particles may contribute to sustained biological darkening throughout the melt season, contrasting with the transient snow algal blooms commonly observed in polar regions. Our study highlights the necessity of integrating region-specific microbial dynamics, which is characterized by the absence of glacier algae and the dominance of mineral-buffered cyanobacterial communities, into glacier mass balance models to improve the accuracy of future projections for Central Asian water resources.</p>
  </abstract>
    
<funding-group>
<award-group id="gs1">
<funding-source>Japan Society for the Promotion of Science</funding-source>
<award-id>25K22868</award-id>
<award-id>24H00260</award-id>
<award-id>22H03731</award-id>
<award-id>21H0457</award-id>
<award-id>20H00196</award-id>
</award-group>
</funding-group>
</article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <label>1</label><title>Introduction</title>
      <p id="d2e192">Glacier and ice sheet constitute a distinct microbe-dominated biome within the Earth system (Anesio and Laybourn-Parry, 2012), harboring up to <inline-formula><mml:math id="M1" display="inline"><mml:mrow><mml:msup><mml:mn mathvariant="normal">10</mml:mn><mml:mn mathvariant="normal">29</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> microbial cells (Irvine-Fynn and Edwards, 2014). The presence of liquid water, which is primarily from surface meltwater during the summer melt season, is one of key limiting factors for microbial activity (Hodson et al., 2008). Seasonal melting transforms glacier surfaces from a snow-covered landscape in winter to a mosaic of habitats in summer, with bare ice prevailing in the ablation zones and snowpack persisting in high-elevation accumulation zones (Stibal et al., 2012a). These snow and bare-ice habitats differ markedly in their physical and chemical properties, leading to distinct microbial communities (Yoshimura et al., 1997; Lutz et al., 2017). However, due to accelerated global glacier shrinkage (Hugonnet et al., 2021), the spatial extent of microbial habitats on glacier and ice sheet surfaces is rapidly diminishing. Therefore, investigating the spatial distribution and abundance of microbial taxa across icy environments is not only critical for understanding the ecological dynamics of glacier surface communities, but also for preserving a biological signature of these unique and increasingly vulnerable ecosystems.</p>
      <p id="d2e206">Algae and cyanobacteria are key cold-adapted photosynthetic microorganisms that play a dominant role on biological carbon accumulation on glacier surfaces during melt season (Anesio et al., 2017). For example, eukaryotic green algae contribute up to 97 % of the total photoautotrophic carbon fixation on the surface of the Greenland Ice Sheet (Yallop et al., 2012). Cyanobacteria are the primary contributors to photosynthetic activity, accounting for approximately 75 %–93 % of carbon fixation within the cryoconite hole on Werenskioldbreen glacier in Svalbard (Stibal and Tranter, 2007).</p>
      <p id="d2e209">In addition to their role in carbon cycling, these microorganisms contribute to the acceleration of snow and ice melt by reducing surface albedo. Pigmented algae, can proliferate during the melt season, leading to visible algal blooms that darken the surface of snow and ice of ice sheet and glacier environments and enhance solar radiation absorption (Williamson et al., 2018; Takeuchi, 2013). Filamentous cyanobacteria produce extracellular polymeric substances (EPS) that facilitate the aggregation of mineral particles, forming dark-colored cryoconite granules (Stibal et al., 2012b; Anesio et al., 2017; Langford et al., 2010), which further lower surface albedo and enhance localized melting on glacier surfaces (Cook et al., 2016; Kohshima et al., 1993; Takeuchi et al., 2018).</p>
      <p id="d2e212">The habitats of algae and cyanobacteria on glacier surfaces are heterogeneous. In cryoconite granules and cryoconite holes on ablation surfaces, filamentous cyanobacteria, particularly members of the order Oscillatoriales, such as <italic>Phormidesmis priestleyi</italic>, <italic>Phormidium</italic> sp., and <italic>Leptolyngbya</italic> sp., are typically dominant and play a crucial role in formation of cryoconite granules (Singh et al., 2021; Segawa et al., 2017; Uetake et al., 2019). On glacier ice surface, algae from the order Zygnematales, including <italic>Ancylonema nordenskiöldii</italic>, <italic>Ancylonema alaskanum</italic>, and <italic>Cylindrocystis br</italic><italic>é</italic><italic>bissonii</italic>, are the predominant taxa (Remias et al., 2012; Ling and Seppelt, 1990; Uetake et al., 2010; Takeuchi, 2013). In contrast, snow surfaces are mainly inhabited by green and red algae belonging to the order Chlamydomonadales, such as <italic>Chlamydomonas</italic> sp., <italic>Chloromonas</italic> sp., and <italic>Sanguina nivaloides</italic> (Davey et al., 2019; Segawa et al., 2018). Given their heterogeneity, it is essential to investigate the altitudinal and seasonal variability of their distribution and abundance to improve our understanding of their contributions to carbon cycling and glacier mass balance.</p>
      <p id="d2e248">Urumqi Glacier No. 1, located in the eastern Tien Shan Mountains, is frequently subject to dust storms that derive from surrounding deserts, resulting in substantial deposition of mineral particles on its ablation surface (Nagatsuka et al., 2014). These dust inputs foster the rapid formation and enlargement of cryoconite granules. A previous investigation has reported high areal coverage and biomass of cryoconite on ablation zone of this glacier, which is far exceeding observed on many Arctic glaciers (Takeuchi and Li, 2008). Within these granules, three morphologically distinct filamentous cyanobacterial taxa have been identified (Segawa et al., 2017); each potentially plays a different role in the initiation and structural development of granules (Chen et al., 2025). Moreover, micro-scale biogeochemical analyses have revealed active nitrogen cycling processes within cryoconite (Segawa et al., 2014, 2020; Murakami et al., 2022), suggesting the presence of nutrient hotspots that sustain microbial life on the oligotrophic supraglacial environment. However, previous studies have focused almost exclusively on the single time-point observations of cryoconite and ablation zone, with limited insight into the temporal dynamics of microbial communities across snow and ice surfaces during the melt season. Furthermore, although hydrological and meteorological observations on this glacier have been conducted since the 1960s (Dong et al., 2012), continuous monitoring of microbial community dynamics has never been carried out, and the influence of biological processes on surface albedo has not been adequately considered. Therefore, conducting continuous observations during the biologically active melt season is essential for improving the accuracy of mass balance models and enhancing our understanding of bio-albedo feedbacks in glacier retreat.</p>
      <p id="d2e251">This study has three main objectives: (1) to investigate the spatial and temporal distribution patterns of algal and cyanobacterial communities on glacial snow and ice surfaces of Urumqi Glacier No. 1; (2) to identify key environmental drivers influencing variations in community structure; and (3) to evaluate the ecological role of phototrophic taxa (algae and cyanobacteria) and their potential impact on glacier surface albedo.</p>
</sec>
<sec id="Ch1.S2">
  <label>2</label><title>Study sites and methods</title>
<sec id="Ch1.S2.SS1">
  <label>2.1</label><title>Study sites</title>
      <p id="d2e269">Urumqi Glacier No. 1, located at 43°06′ N and 86°49′ E, lies within the Tien Shan Mountains of the Xinjiang Uyghur Autonomous Region in western China (Fig. 1a). This northeast-facing glacier spans elevations from 3752 to 4445 m above sea level (m a.s.l.). This glacier lost approximately 20 % of its volume between 1962 and 2003, and it split into eastern and western branches in 1993 as a result of its continued retreat (Ye et al., 2005). The total catchment area is approximately 1.618 <inline-formula><mml:math id="M4" display="inline"><mml:mrow class="unit"><mml:msup><mml:mi mathvariant="normal">km</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> (Yue et al., 2022). Mass accumulation primarily occurs during the summer months, corresponding with peak precipitation rates. Hourly meteorological data, including air temperature, downwards solar radiation, precipitation, and snowmelt (in water equivalent), were obtained from ERA5-Land (<inline-formula><mml:math id="M5" display="inline"><mml:mrow><mml:mn mathvariant="normal">0.1</mml:mn><mml:mi mathvariant="italic">°</mml:mi><mml:mo>×</mml:mo><mml:mn mathvariant="normal">0.1</mml:mn><mml:mi mathvariant="italic">°</mml:mi></mml:mrow></mml:math></inline-formula> resolution, 2 m above surface, <uri>https://cds.climate.copernicus.eu/datasets/reanalysis-era5-land?tab=download</uri>, last access: 16 July   2025) for 1 July–31 August 2013, and converted to daily means by averaging hourly values (Fig. 2). The mean annual equilibrium line altitude (ELA) in 2013 was 4240 m a.s.l. (<uri>https://wgms.ch/products_ref_glaciers/urumqi/</uri>, last access: 7  March 2026). This region is frequently influenced by dust storm activity due to the surrounding major deserts, with dust primarily originating from the Taklimakan Desert (Takeuchi et al., 2011; Li et al., 2010; Nagatsuka et al., 2014). The glacier’s ablation zone is notably characterized by the widespread presence of cryoconite granules, with a mean dry weight of 335 <inline-formula><mml:math id="M6" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> and an organic matter content of 9.4 % <inline-formula><mml:math id="M7" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.6 % (Takeuchi and Li, 2008). Cryoconite holes are generally absent from the glacier surface (Takeuchi and Li, 2008).</p>

      <fig id="F1" specific-use="star"><label>Figure 1</label><caption><p id="d2e362">Location maps and photographs of Urumqi Glacier No. 1. <bold>(a)</bold> Location of Urumqi Glacier No. 1 in the Tien Shan Mountains. <bold>(b)</bold> Map of sampling sites (S1–S6) in this study. <bold>(c)</bold> Photographs of Urumqi Glacier No. 1 across five sampling periods in 2013.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f01.jpg"/>

        </fig>

      <fig id="F2" specific-use="star"><label>Figure 2</label><caption><p id="d2e382">Meteorological datasets of Urumqi Glacier No. 1 during July and August in 2013. P1–P5 denote sampling period.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f02.png"/>

        </fig>

</sec>
<sec id="Ch1.S2.SS2">
  <label>2.2</label><title>Methods</title>
<sec id="Ch1.S2.SS2.SSS1">
  <label>2.2.1</label><title>Sampling collection</title>
      <p id="d2e406">Field investigations were conducted five times in 2013, specifically on 8–14 July (P1), 20–21 July (P2), 2–3 August (P3), 15–16 August (P4), and 24–26 August (P5), across six sites on different altitudes (S1–S6, Figs. 1b, S1 in the Supplement). During P1, S1–S4 were characterized by exposed ice surfaces, while S5 and S6 remained snow-covered (Fig. 1c). In the subsequent four sampling periods, ice surfaces extended upslope, resulting in S1 to S5 being classified as ice surfaces, with only S6 retaining a snow cover (Fig. 1c). Ice surface was characterized by widespread, dispersed cryoconite material, consistent with the patterns reported by Takeuchi and Li (2008). Surface ice and snow samples containing dispersed cryoconite were collected along the eastern branch of Urumqi Glacier No. 1 using a pre-cleaned stainless-steel scoop. Each sample covered an area of approximately 30–225 <inline-formula><mml:math id="M8" display="inline"><mml:mrow class="unit"><mml:msup><mml:mi mathvariant="normal">cm</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> and had a thickness of 1–2 cm (Table S1 in the Supplement). For subsequent analysis, three to five samples were collected from randomly selected surface areas at each site. To preserve biological activity, samples were melted and fixed with a 3 % formalin solution in sterile 30 mL polyethylene bottles (IBOY, AS ONE, Japan). Additionally, one sample per site was collected and kept frozen without fixative for taxonomic identification of algal and cyanobacterial species. All samples were subsequently delivered to a laboratory at Chiba University for further analysis within six months of sampling.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS2">
  <label>2.2.2</label><title>Morphological identification of algae and cyanobacteria</title>
      <p id="d2e429">Algal and cyanobacteria taxa were identified based on morphological observations using an optical microscope. To loosen sedimentary particles, each sample was ultrasonicated for 10 min. For each observed taxon, morphological characteristics and sizes, were recorded and compared with descriptions in previous studies (Takeuchi and Kohshima, 2004; Takeuchi et al., 2019; Segawa et al., 2017). Algae were identified using optical microscopy (BX51, Olympus, Japan). In contrast, cyanobacteria were highly difficult to distinguish from the abundant mineral particles and organic matter present in the samples under standard transmitted light; therefore, epifluorescence microscopy was employed for their detection. Cells were photographed at 400<inline-formula><mml:math id="M9" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> magnification using randomly selected fields of view. Cell dimensions were measured from digital images using ImageJ software (National Institutes of Health, USA). For each taxon, approximately 60–100 cells were measured, and the mean values were used for subsequent analyses. Because filamentous cyanobacteria consisted of very small cells, images were captured at 1000<inline-formula><mml:math id="M10" display="inline"><mml:mo>×</mml:mo></mml:math></inline-formula> magnification to determine the average cell width and length. The biovolume of a single cell was calculated from the volumes of geometric analogs of cell morphology: cyanobacterial cells were modeled as cylinders, and algal cells were represented as ellipsoids or spheres.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS3">
  <label>2.2.3</label><title>Quantification of algal and cyanobacterial biovolume-based biomass</title>
      <p id="d2e454">Cell abundance and biovolume-based biomass of algae and cyanobacteria at each sampling site was quantified by direct optical microscopic cell counting. Only cells showing chlorophyll autofluorescence were considered viable phototrophic microorganisms and included in the counts. A volume of 2–100 mL of meltwater was filtered through a polytetrafluoroethylene (PTFE) membrane filter (pore size 0.45 <inline-formula><mml:math id="M11" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>; JHWP01300, Merck Millipore, Germany), and cells retained on the filter were enumerated using an optical microscope (BX51, Olympus, Japan) by counting 1–3 randomly selected transects per filter. Each sample was counted in 3–5 times to ensure reproducibility. Unicellular taxa were counted as individual cells. For filamentous cyanobacteria, which cannot be counted as individual cells due to their elongated trichomes, we quantified their abundance by counting them in standardized length units of 12.5 <inline-formula><mml:math id="M12" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi></mml:mrow></mml:math></inline-formula>m using a calibrated microscope grid. This length unit corresponds to the average size of a single cell within the filament. These length counts were then converted to cell numbers based on the average cell dimensions determined for each taxon. Cell concentrations (<inline-formula><mml:math id="M13" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">cells</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">mL</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, Table S2) were calculated based on the average cell counts and the volume of water filtered. The total biovolume (mL) of snow and ice algae in each sample was calculated as the product of cell concentration (<inline-formula><mml:math id="M14" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">cells</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">mL</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) and the mean cell volume of each taxon (<inline-formula><mml:math id="M15" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msup></mml:mrow></mml:math></inline-formula> per cell). Total biovolume-based biomass (<inline-formula><mml:math id="M16" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) of algae and cyanobacteria was then estimated by biovolume (cell volume) per unit surface area The biovolume-based community composition (proportion) at each site was expressed as the relative abundance of each taxon to the total biovolume-based biomass. Mean values and standard deviations were calculated based on replicate samples collected from different surface areas at each site.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS4">
  <label>2.2.4</label><title>Major chemical solutes measurement</title>
      <p id="d2e550">Major soluble ions in snow samples, including anions of <inline-formula><mml:math id="M17" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M18" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Cl</mml:mi><mml:mo>-</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M19" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> and cations of <inline-formula><mml:math id="M20" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M21" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">K</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M22" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Na</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M23" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M24" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Ca</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, were analyzed using an ion chromatography system (ICS-1100, Thermo Fisher Scientific, USA). Prior to analysis, melted samples were filtered through ion-free chromatographic discs (Chromate disk, pore size: 0.45 <inline-formula><mml:math id="M25" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>, GL Science, Japan) to eliminate particulate matter.</p>
      <p id="d2e667">For anion analysis, a Dionex IonPac AS12A analytical column paired with an AG12A guard column was employed. The eluent consisted of a mixture of 2.7 mM <inline-formula><mml:math id="M26" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">Na</mml:mi><mml:mn mathvariant="normal">2</mml:mn></mml:msub><mml:msub><mml:mi mathvariant="normal">CO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula> and 0.3 mM <inline-formula><mml:math id="M27" display="inline"><mml:mrow class="chem"><mml:msub><mml:mi mathvariant="normal">NaHCO</mml:mi><mml:mn mathvariant="normal">3</mml:mn></mml:msub></mml:mrow></mml:math></inline-formula>, delivered at a flow rate of 1.5 <inline-formula><mml:math id="M28" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">mL</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">min</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. For cation analysis, a Dionex IonPac CS12A column was used with 20 mM methanesulfonic acid as the eluent, operating at a flow rate of 1.0 <inline-formula><mml:math id="M29" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">mL</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">min</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. The reported ionic composition represents only the major dissolved ions analyzed in this study and does not constitute a complete ionic charge balance, as dissolved species such as bicarbonate (<inline-formula><mml:math id="M30" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">HCO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>) were not included in the analytical protocol.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS5">
  <label>2.2.5</label><title>Determination of mineral and organic matter loads</title>
      <p id="d2e753">The mass of organic and mineral matter per unit area of samples collected during P5 were determined using a loss-on-ignition (LOI) method. Samples were dried in pre-weighed crucibles at an electrical dryer (DO-450FA, As One, Japan) at 60 <inline-formula><mml:math id="M31" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">°</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula> for 24–48 h until a constant mass was achieved. After cooling to room temperature, the samples were weighed to obtain the dry mass (<inline-formula><mml:math id="M32" display="inline"><mml:mrow><mml:msub><mml:mi>m</mml:mi><mml:mi mathvariant="normal">d</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>). The dried samples were then combusted at 500 <inline-formula><mml:math id="M33" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">°</mml:mi><mml:mi mathvariant="normal">C</mml:mi></mml:mrow></mml:math></inline-formula> for 3 h in an electric furnace and reweighed after cooling to determine the combusted mass (<inline-formula><mml:math id="M34" display="inline"><mml:mrow><mml:msub><mml:mi>m</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>). Organic matter mass was calculated as the mass loss during combustion (<inline-formula><mml:math id="M35" display="inline"><mml:mrow><mml:msub><mml:mi>m</mml:mi><mml:mi mathvariant="normal">d</mml:mi></mml:msub><mml:mo>-</mml:mo><mml:msub><mml:mi>m</mml:mi><mml:mi mathvariant="normal">c</mml:mi></mml:msub></mml:mrow></mml:math></inline-formula>). The mineral fraction was estimated as the remaining mass after combustion. Five replicate samples were analyzed for each sampling site, and the mean value was calculated from the replicate measurements.</p>
</sec>
<sec id="Ch1.S2.SS2.SSS6">
  <label>2.2.6</label><title>Statistical data analysis</title>
      <p id="d2e824">Dissimilarities in community composition of algae and cyanobacteria, as well as in ion composition across sampling period and surface status (ice vs. snow), were assessed using permutational multivariate analysis of variance (PERMANOVA) based on Bray–Curtis distance matrices, implemented with the adonis function in the R package “vegan” (Oksanen et al., 2010). Spearman's rank correlation analysis was conducted in OriginPro to examine relationships between algal/cyanobacterial biovolume-based biomass and chemical variables. A two-way analysis of variance (two-way ANOVA) was used to evaluate the effects of surface status and sampling period on phototrophic biovolume-based biomass. Differences in major ion concentrations and mineral loads among sampling periods and surface conditions were evaluated using one-way analysis of variance (one-way ANOVA). All univariate statistical analyses were performed in OriginPro. Statistical significance was determined at <inline-formula><mml:math id="M36" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>.</p>
</sec>
</sec>
</sec>
<sec id="Ch1.S3">
  <label>3</label><title>Results</title>
<sec id="Ch1.S3.SS1">
  <label>3.1</label><title>Observed algae and cyanobacteria on the glacier surface</title>
      <p id="d2e856">Two taxa of algae and six taxa of cyanobacteria were identified on the glacier surface through microscopic observation (Table 1, Fig. 3). The morphological characteristic of each taxon was described as follows, in conjunction with findings from previous DNA-based studies (Segawa et al., 2017, 2023). Molecular analyses previously detected a total of 20 cyanobacterial operational taxonomic units (OTUs) on the glacier surface. These previous molecular frameworks were utilized as a reference to guide our morphological classification of the dominant active taxa.</p>

<table-wrap id="T1" specific-use="star"><label>Table 1</label><caption><p id="d2e862">Morphological Characteristics of Identified Algae and Cyanobacteria.</p></caption><oasis:table frame="topbot"><oasis:tgroup cols="4">
     <oasis:colspec colnum="1" colname="col1" align="justify" colwidth="70pt"/>
     <oasis:colspec colnum="2" colname="col2" align="left"/>
     <oasis:colspec colnum="3" colname="col3" align="justify" colwidth="85pt"/>
     <oasis:colspec colnum="4" colname="col4" align="justify" colwidth="135pt"/>
     <oasis:thead>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left">Phototrophic taxa</oasis:entry>
         <oasis:entry colname="col2">Cell morphology</oasis:entry>
         <oasis:entry colname="col3" align="left">Size (<inline-formula><mml:math id="M37" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>, mean <inline-formula><mml:math id="M38" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> SD)</oasis:entry>
         <oasis:entry colname="col4" align="left">Metabarcoding data (reference)</oasis:entry>
       </oasis:row>
     </oasis:thead>
     <oasis:tbody>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left"><italic>Chloromonadinia</italic> species</oasis:entry>
         <oasis:entry colname="col2">Sphere</oasis:entry>
         <oasis:entry colname="col3" align="left">Diameter: 16.0 <inline-formula><mml:math id="M39" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.8</oasis:entry>
         <oasis:entry colname="col4" align="left"><italic>Chloromonadinia</italic> species (Segawa et al., 2023)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left"><italic>Cylindrocystis brébissonii</italic></oasis:entry>
         <oasis:entry colname="col2">Cylinder</oasis:entry>
         <oasis:entry colname="col3" align="left">Length: 28.3 <inline-formula><mml:math id="M40" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.0; Width: 17.6 <inline-formula><mml:math id="M41" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.9</oasis:entry>
         <oasis:entry colname="col4" align="left">No corresponding data</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left">Oscillatoriaceae cyanobacterium 1</oasis:entry>
         <oasis:entry colname="col2">Filamentous cell</oasis:entry>
         <oasis:entry colname="col3" align="left">Trichomes: 15–80 Length: 2.0 <inline-formula><mml:math id="M42" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3 Width: 1.6 <inline-formula><mml:math id="M43" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.2</oasis:entry>
         <oasis:entry colname="col4" align="left"><italic>Pseudanabaena</italic> (Segawa et al., 2017)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left">Oscillatoriaceae cyanobacterium 2</oasis:entry>
         <oasis:entry colname="col2">Filamentous cell</oasis:entry>
         <oasis:entry colname="col3" align="left">Trichomes: 20–430 Length: 3.2 <inline-formula><mml:math id="M44" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.8 Width: 3.1 <inline-formula><mml:math id="M45" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.5</oasis:entry>
         <oasis:entry colname="col4" align="left"><italic>Microcoleus</italic> (Segawa et al., 2017)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left">Oscillatoriaceae cyanobacterium 3</oasis:entry>
         <oasis:entry colname="col2">Filamentous cell</oasis:entry>
         <oasis:entry colname="col3" align="left">Trichomes: 20–260 Length: 2.0 <inline-formula><mml:math id="M46" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3 Width: 1.5 <inline-formula><mml:math id="M47" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.2</oasis:entry>
         <oasis:entry colname="col4" align="left">Unclassified; <italic>Oscillatoriales</italic>;  <italic>Geitlerinema</italic> (Segawa et al., 2017)</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left">Chroococcaceae cyanobacterium 1</oasis:entry>
         <oasis:entry colname="col2">Sphere</oasis:entry>
         <oasis:entry colname="col3" align="left">Diameter: 3.8 <inline-formula><mml:math id="M48" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.6</oasis:entry>
         <oasis:entry colname="col4" align="left">No corresponding data</oasis:entry>
       </oasis:row>
       <oasis:row rowsep="1">
         <oasis:entry colname="col1" align="left">Chroococcaceae cyanobacterium 2</oasis:entry>
         <oasis:entry colname="col2">Sphere</oasis:entry>
         <oasis:entry colname="col3" align="left">Diameter: 3.9 <inline-formula><mml:math id="M49" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.6</oasis:entry>
         <oasis:entry colname="col4" align="left">No corresponding data</oasis:entry>
       </oasis:row>
       <oasis:row>
         <oasis:entry colname="col1" align="left">Chroococcaceae cyanobacterium 3</oasis:entry>
         <oasis:entry colname="col2">Sphere</oasis:entry>
         <oasis:entry colname="col3" align="left">Diameter: 2.7 <inline-formula><mml:math id="M50" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.1</oasis:entry>
         <oasis:entry colname="col4" align="left">No corresponding data</oasis:entry>
       </oasis:row>
     </oasis:tbody>
   </oasis:tgroup></oasis:table></table-wrap>

      <fig id="F3" specific-use="star"><label>Figure 3</label><caption><p id="d2e1153">Photographs of algae and cyanobacteria observed on surface of Urumqi Glacier No. 1. <bold>(a)</bold> <italic>Cylindrocystis brébissonii</italic>; <bold>(b)</bold> <italic>Chloromonadinia</italic> species; <bold>(c)</bold> Oscillatoriaceae cyanobacterium 1; <bold>(d)</bold> Oscillatoriaceae cyanobacterium 2; <bold>(e)</bold> Oscillatoriaceae cyanobacterium 3; <bold>(f)</bold> Chroococcaceae cyanobacterium 1; <bold>(g)</bold> Chroococcaceae cyanobacterium 2; <bold>(h)</bold> Chroococcaceae cyanobacterium 3. Scale bar <inline-formula><mml:math id="M51" display="inline"><mml:mo>=</mml:mo></mml:math></inline-formula> 10 <inline-formula><mml:math id="M52" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f03.jpg"/>

        </fig>

<sec id="Ch1.S3.SS1.SSS1">
  <label>3.1.1</label><title>Algae</title>
</sec>
<sec id="Ch1.S3.SS1.SSSx1" specific-use="unnumbered">
  <title>(1) <bold><italic>Chloromonadinia</italic></bold> <bold>species</bold></title>
      <p id="d2e1232">Cells were spherical in shape and lacked visible pyrenoids in the chloroplasts. Intracellular pigments appeared green and red, and all observed cells were in the zygote stage. Mean cell diameter was 16.0 <inline-formula><mml:math id="M53" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.8 <inline-formula><mml:math id="M54" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>.</p>
</sec>
<sec id="Ch1.S3.SS1.SSSx2" specific-use="unnumbered">
  <title>(2) <bold><italic>Cylindrocystis brébissonii</italic></bold></title>
      <p id="d2e1262">Cells were cylindrical with rounded apices, containing two chloroplasts each with a central pyrenoid. However, only one chloroplast was observed in short, divided cells. Cells measured 28.3 <inline-formula><mml:math id="M55" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 6.0 <inline-formula><mml:math id="M56" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length and 17.6 <inline-formula><mml:math id="M57" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.9 <inline-formula><mml:math id="M58" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in width.</p>
</sec>
<sec id="Ch1.S3.SS1.SSS2">
  <label>3.1.2</label><title>Cyanobacteria</title>
</sec>
<sec id="Ch1.S3.SS1.SSSx3" specific-use="unnumbered">
  <title>(1) <bold>Oscillatoriaceae (Osc.) cyanobacterium 1</bold></title>
      <p id="d2e1316">Trichomes lacked a sheath, and clear constrictions were visible between adjacent cells. Trichomes were 15–80 <inline-formula><mml:math id="M59" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length. Cells measured 2.0 <inline-formula><mml:math id="M60" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.4 <inline-formula><mml:math id="M61" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length and 1.6 <inline-formula><mml:math id="M62" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.2 <inline-formula><mml:math id="M63" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in width.</p>
</sec>
<sec id="Ch1.S3.SS1.SSSx4" specific-use="unnumbered">
  <title>(2) <bold>Oscillatoriaceae cyanobacterium 2</bold></title>
      <p id="d2e1372">Trichome were enclosed within a colorless mucilaginous sheath. Green intracellular granules were observed within the cells. Trichomes were 20–430 <inline-formula><mml:math id="M64" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length. Cells measured 3.2 <inline-formula><mml:math id="M65" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.8 <inline-formula><mml:math id="M66" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length and 3.1 <inline-formula><mml:math id="M67" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.5 <inline-formula><mml:math id="M68" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in width.</p>
</sec>
<sec id="Ch1.S3.SS1.SSSx5" specific-use="unnumbered">
  <title>(3) <bold>Oscillatoriaceae cyanobacterium 3</bold></title>
      <p id="d2e1429">Trichome were surrounded by a colorless mucilaginous sheath, without conspicuous internal structures. Trichomes were 20–260 <inline-formula><mml:math id="M69" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length. Cells measured 2.0 <inline-formula><mml:math id="M70" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.3 <inline-formula><mml:math id="M71" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in length and 1.5 <inline-formula><mml:math id="M72" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.2 <inline-formula><mml:math id="M73" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula> in width.</p>
</sec>
<sec id="Ch1.S3.SS1.SSSx6" specific-use="unnumbered">
  <title>(4) <bold>Chroococcaceae (Chr.) cyanobacterium 1</bold></title>
      <p id="d2e1485">Spherical cells were surrounded by with brown or yellow mucilaginous sheaths and occurred as solitary or paired cells forming small colonies. Mean cell diameter was 3.8 <inline-formula><mml:math id="M74" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.6 <inline-formula><mml:math id="M75" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>.</p>
</sec>
<sec id="Ch1.S3.SS1.SSSx7" specific-use="unnumbered">
  <title>(5) <bold>Chroococcaceae cyanobacterium 2</bold></title>
      <p id="d2e1514">Spherical paired cells without apparent colonies. Mean cell diameter was 3.9 <inline-formula><mml:math id="M76" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 0.6 <inline-formula><mml:math id="M77" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>.</p>
</sec>
<sec id="Ch1.S3.SS1.SSSx8" specific-use="unnumbered">
  <title>(6) <bold>Chroococcaceae cyanobacterium 3</bold></title>
      <p id="d2e1543">Spherical cells with a mean diameter of 2.7 <inline-formula><mml:math id="M78" display="inline"><mml:mo>±</mml:mo></mml:math></inline-formula> 1.1 <inline-formula><mml:math id="M79" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:mrow></mml:math></inline-formula>.</p>
</sec>
</sec>
<sec id="Ch1.S3.SS2">
  <label>3.2</label><title>Seasonal and spatial variations in the total biomass of algae and cyanobacteria</title>
      <p id="d2e1572">The total biovolume-based biomass of algae and cyanobacteria on the glacier surface remained relatively stable through the melt season (two-way ANOVA, <inline-formula><mml:math id="M80" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.62</mml:mn><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>, Fig. 4). However, a marked increase in total biomass was observed when the snow surface transitioned to bare ice at the midstream sites (S4 and S5). At S4, biomass increased markedly from P1 to P2 (from 4.7 to 419.1 <inline-formula><mml:math id="M81" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). At S5, although the biomass in P1 (3.7 <inline-formula><mml:math id="M82" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) was not significantly different from that in P2 (1.2 <inline-formula><mml:math id="M83" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), a significant increase was observed in P3, with biomass reaching 278.3 <inline-formula><mml:math id="M84" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. During P5, biomass on ice surface (S1–S5) remained at comparable levels. Overall, the total biovolume-based biomass on the ice surface was significantly higher than that on the snow surface (two-way ANOVA, <inline-formula><mml:math id="M85" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>=</mml:mo><mml:mn mathvariant="normal">0.03</mml:mn><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>).</p>

      <fig id="F4"><label>Figure 4</label><caption><p id="d2e1683">Seasonal and spatial variations in the total biovolume-based biomass of algae and cyanobacteria on Urumqi Glacier No. 1 from July to August 2013. The blue dashed line represents the boundary between the snow and ice surface.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f04.png"/>

        </fig>

</sec>
<sec id="Ch1.S3.SS3">
  <label>3.3</label><title>Spatiotemporal changes of algal and cyanobacterial community composition on glacier surfaces</title>
      <p id="d2e1700">The relative dominance of algae and cyanobacteria varied primarily with surface status rather than sampling period (Fig. 5). PERMANOVA analysis detected no significant differences in community composition among sampling periods (<inline-formula><mml:math id="M86" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>), whereas significant differences were observed between snow-covered and ice surfaces (<inline-formula><mml:math id="M87" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>). Across all sampling periods, snow surfaces were consistently dominated by algal taxa, primarily <italic>Chloromonadinia</italic> species, whereas cyanobacteria predominated on bare ice surfaces.</p>

      <fig id="F5"><label>Figure 5</label><caption><p id="d2e1732">Seasonal variations in the biovolume-based community composition of algae and cyanobacteria at sampling sites (S1–S6) across five sampling periods (P1–P5). The dashed line represents the boundary between the snow and ice surface.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f05.png"/>

        </fig>

      <p id="d2e1741">A clear upstream shift in cyanobacterial dominance accompanied the seasonal expansion of bare ice. During P1, filamentous cyanobacteria were dominant on downstream ice-covered sites (S1–S3), accounting for 61 %–75 % of the total biovolume-based biomass, whereas the snow-covered upstream sites (S4–S6) were prevailed by <italic>Chloromonadinia</italic> species, contributing 65 %–92 % in biovolume-based community composition. By P2, cyanobacterial dominance had expanded upstream and Chloromonadinia species remained dominant only at S5 and S6. From P3 onward, filamentous cyanobacteria consistently dominated sites S1–S5, while <italic>Chloromonadinia</italic> species remained dominant solely at the uppermost site (S6). The only exception occurred during P4, when filamentous cyanobacteria dominated all sites, accounting for 61 %–84 % of the total biomass.</p>
      <p id="d2e1751">Among the algal taxa, <italic>Chloromonadinia</italic> species were the principal constituents of snow communities throughout the study, accounting for 16 %–92 % of the total biomass. In contrast, <italic>Cylindrocystis brébissonii</italic> was detected exclusively on ice surfaces and occurred sporadically at one or two sites during each sampling period, representing less than 1.5 % of the total biomass.</p>
      <p id="d2e1760">Filamentous Oscillatoriaceae cyanobacteria constituted the dominant component of ice-surface communities during sampling period. Osc. cyanobacterium 1 showed a clear preference for ice surfaces, with biomass generally rising from P1 to P4, particularly at mid- to up-glacier ice sites. In contrast, its biomass on snow surfaces remained negligible throughout the sampling period, rarely exceeding 0.1 <inline-formula><mml:math id="M88" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> (Fig. S2).</p>
      <p id="d2e1782">Osc. cyanobacteria 2 and 3 were the most abundant cyanobacterial taxa, constituting 65 %–95 % of the total cyanobacterial biovolume-based biomass across all ice sites and sampling periods. Their biomass increased progressively from P1 to P4, with the highest values recorded at sites S3 and S4 during P4, where Osc. cyanobacterium 2 exceeded 300 <inline-formula><mml:math id="M89" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> and Osc. cyanobacterium 3 surpassed 470 <inline-formula><mml:math id="M90" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>. From P4 onward, a distinct spatial pattern emerged: Osc. cyanobacterium 2 dominated the downstream sites (S1–S2), whereas Osc. cyanobacterium 3 became dominant at the upstream sites (S3–S5). In contrast, both taxa showed very low biovolume-based biomass on snow-covered surfaces, with biomass consistently below 1 <inline-formula><mml:math id="M91" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>.</p>
      <p id="d2e1842">Among the unicellular cyanobacteria, Chr. cyanobacterium 1 showed a noticeable biomass increase by P4 on ice, reaching up to <inline-formula><mml:math id="M92" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">30</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M93" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> at S3 and S4. Chr. cyanobacteria 2 and 3 maintained relatively low abundance levels throughout all sampling sites and periods, with slight elevations observed on ice during P4. All three Chroococcaceae taxa were almost absent on snow surfaces (<inline-formula><mml:math id="M94" display="inline"><mml:mrow><mml:mtext>biomass</mml:mtext><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.13</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M95" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>).</p>
</sec>
<sec id="Ch1.S3.SS4">
  <label>3.4</label><title>Variations in chemical conditions across the sampling period and surface status</title>
      <p id="d2e1913">The concentrations of major ions showed notable temporal variation throughout the five sampling periods (Fig. 6). <inline-formula><mml:math id="M96" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M97" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M98" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">K</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M99" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> concentrations temporally varied significantly among sampling periods (one-way ANOVA, <inline-formula><mml:math id="M100" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>). <inline-formula><mml:math id="M101" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M102" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> both peaked in P1 (<inline-formula><mml:math id="M103" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">12.9</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M104" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">6.8</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M105" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, respectively), declined sharply in P2, and showed secondary increases in P5. In contrast, <inline-formula><mml:math id="M106" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">K</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> remained stable in early periods (<inline-formula><mml:math id="M107" display="inline"><mml:mrow><mml:mo>∼</mml:mo><mml:mn mathvariant="normal">5</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M108" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) before declining to its lowest level in P5 (<inline-formula><mml:math id="M109" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">1.7</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M110" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). <inline-formula><mml:math id="M111" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> exhibited elevated concentrations in P1 and P3 (<inline-formula><mml:math id="M112" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">20.3</mml:mn></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M113" display="inline"><mml:mrow><mml:mo>=</mml:mo><mml:mn mathvariant="normal">25.9</mml:mn></mml:mrow></mml:math></inline-formula> <inline-formula><mml:math id="M114" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), dropped markedly to 8.6 <inline-formula><mml:math id="M115" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> in P4, and partially rebounded to 11.3 <inline-formula><mml:math id="M116" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> in P5.</p>

      <fig id="F6" specific-use="star"><label>Figure 6</label><caption><p id="d2e2215">Spatial and temporal variations in major ion concentrations at six sampling sites (S1–S6) across five sampling periods (P1–P5). Red dashed line represents the boundary between the snow and ice surface.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f06.png"/>

        </fig>

      <p id="d2e2224">Significant differences in ion concentrations were also observed between surface status (ice vs. snow) (one-way ANOVA, <inline-formula><mml:math id="M117" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.01</mml:mn></mml:mrow></mml:math></inline-formula>, Fig. 6b). Ice surfaces consistently hold higher mean concentrations of crustally derived ions, including <inline-formula><mml:math id="M118" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Ca</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> (125.5 vs. 22.6 <inline-formula><mml:math id="M119" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), <inline-formula><mml:math id="M120" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> (20.6 vs. 5.9 <inline-formula><mml:math id="M121" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), <inline-formula><mml:math id="M122" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Na</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> (12.5 vs. 5.3 <inline-formula><mml:math id="M123" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) and <inline-formula><mml:math id="M124" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">K</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula> (4.9 vs. 1.3 <inline-formula><mml:math id="M125" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>). In contrast, snow surfaces showed higher concentrations of <inline-formula><mml:math id="M126" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (2.3 vs. 6.0 <inline-formula><mml:math id="M127" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), <inline-formula><mml:math id="M128" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">SO</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>-</mml:mo></mml:mrow></mml:msubsup></mml:mrow></mml:math></inline-formula> (6.3 vs. 10.1 <inline-formula><mml:math id="M129" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>), and <inline-formula><mml:math id="M130" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> (2.6 vs. 8.0 <inline-formula><mml:math id="M131" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>).</p>
</sec>
<sec id="Ch1.S3.SS5">
  <label>3.5</label><title>Mineral and organic matter loads on glacier surface</title>
      <p id="d2e2476">Mineral matter constituted the dominant fraction (<inline-formula><mml:math id="M132" display="inline"><mml:mrow><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">88.2</mml:mn></mml:mrow></mml:math></inline-formula> %) in samples collected on ice surface (S1–S5) during P5, accounting for 185.7–314.6 <inline-formula><mml:math id="M133" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">g</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, whereas organic matter represented a much smaller proportion, ranging from 15.5 to 42.0 <inline-formula><mml:math id="M134" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">g</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> (Table S4). No significant differences in mineral fractions were observed among sampling sites (one-way ANOVA, <inline-formula><mml:math id="M135" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&gt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>), whereas organic fractions varied significantly among sites (one-way ANOVA, <inline-formula><mml:math id="M136" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>).</p>
</sec>
</sec>
<sec id="Ch1.S4">
  <label>4</label><title>Discussion</title>
<sec id="Ch1.S4.SS1">
  <label>4.1</label><title>Algal community dynamics in response to glacier surface transition</title>
      <p id="d2e2564">The biomass of snow/glacier algae on Urumqi Glacier No. 1 remained consistently low with minimal temporal variation, suggesting that algal proliferation is highly constrained in this environment. Previous studies have shown that glacier algal blooms on the Greenland Ice Sheet are strongly promoted by the availability of mineral phosphorus released from aeolian dust (McCutcheon et al., 2021). Despite the abundance of mineral particles on the Urumqi Glacier No. 1, glacier algae kept a low biomass on the surface, suggesting that factors other than dust abundance, such as phosphorus bioavailability or local environmental conditions, may limit glacier algal establishment in this region. <italic>Chloromonadinia</italic> species was found on both snow and ice but showed a clear preference for snow, aligning with its classification as a snow-environment specialist (Takeuchi, 2001), similar to observations in the Himalayas (Yoshimura et al., 1997) and Altai Mountains (Takeuchi et al., 2006). All observed Chloromonadinia cells were in the zygote stage, characterized by orange-red pigmentation. All observed <italic>Chloromonadinia</italic> cells were in the zygote stage, characterized by orange-red pigmentation. The exclusive occurrence of zygotes indicates that this taxon was present predominantly in a dormant or resistant life stage rather than as an actively growing population.</p>
      <p id="d2e2573">Conversely, the green alga <italic>C. brébissonii</italic> was restricted to ice surfaces. Despite its presence, its sporadic and low abundance suggest it functions as an ice-specialist that fails to establish stable, large-scale populations on this glacier, contrasting with earlier classifications that often regard certain <italic>Cylindrocystis</italic> strains as opportunists with broader habitat ranges (Kol, 1942; Remias et al., 2012).</p>
      <p id="d2e2582">On this glacier, the role of algae in surface darkening is habitat-dependent. On snow, despite low biomass, <italic>Chloromonadinia</italic> species is likely the primary biological agent for albedo reduction due to the absence of cryoconite. However, on bare ice, the direct contribution of eukaryotic algae to surface darkening may be secondary to that of cyanobacteria and mineral particles, primarily due to the overwhelming biomass dominance of filamentous cyanobacteria and the heavy loading of lithogenic dust observed throughout the melt season. This is consistent with studies suggesting that while snow algae can significantly lower albedo in the early melt season, their impact is often overshadowed by other light-absorbing particles (e.g., cryoconite) once the ice is exposed (Lutz et al., 2016; Di Mauro et al., 2020).</p>
</sec>
<sec id="Ch1.S4.SS2">
  <label>4.2</label><title>Phylogenetic lines of the cyanobacterial microscopic morphotypes</title>
      <p id="d2e2596">Previous DNA metabarcoding studies on Urumqi Glacier No. 1 detected approximately 8 cyanobacterial operational taxonomic units (OTUs) (Segawa et al., 2017), whereas microscopic observation in this study identified six cyanobacterial morphotypes and two algal taxa. This numerical difference reflects the complementary nature of the two approaches rather than an inconsistency between the datasets. DNA metabarcoding is highly sensitive and captures the full taxonomic inventory of glacier microorganisms, including rare, dormant, or transient taxa introduced by atmospheric deposition. In contrast, microscopic observation coupled with chlorophyll autofluorescence selectively captures structurally intact, pigment-bearing phototrophs, enabling the direct quantification of cell abundance and biomass.</p>
      <p id="d2e2599">Consistent with previous molecular data, our dominant filamentous morphotypes corresponded with major filamentous cyanobacterial OTUs previously reported from these sites, such as <italic>Microcoleus</italic>, <italic>Pseudanabaena</italic>, and <italic>Geitlerinema</italic> (Table 1; Segawa et al., 2017). Despite the greater OTU richness revealed by high-throughput sequencing, the bulk of the phototrophic biomass during the melt season was contributed by only two dominant Oscillatoriaceae morphotypes, which drove the clear spatial and seasonal succession observed across the glacier. These findings demonstrate that while DNA metabarcoding provides a comprehensive taxonomic inventory, microscopic quantification is indispensable for identifying the specific dominant taxa responsible for actual biomass accumulation and community dynamics. Taken together, integrating molecular checklists with morphological biomass estimation yields a more holistic understanding of supraglacial phototrophic communities.</p>
</sec>
<sec id="Ch1.S4.SS3">
  <label>4.3</label><title>Cyanobacterial dominance and its role in surface darkening</title>
      <p id="d2e2619">In contrast to the ephemeral nature of snow algae, the cyanobacterial community on Urumqi Glacier No. 1 exhibited remarkable temporal stability in total biovolume-based biomass, albeit with significant spatial and taxonomic shifts. While unicellular Chroococcaceae maintained low biomass, filamentous cyanobacteria (Oscillatoriaceae) sustained dominance on ice surfaces throughout the melt season. This persistent presence suggests their potential role in surface darkening through two primary pathways: direct organic pigmentation and the structural aggregation of mineral particles into stable, dark cryoconite granules (Takeuchi, 2009, 2013).</p>
      <p id="d2e2622">The spatial distribution of these dominant filamentous cyanobacteria revealed a distinct altitudinal zonation from P4 onwards, despite uniform geochemical characteristics across the glacier. Osc. cyanobacterium 2 dominated the downstream sites (S1–S2), whereas Osc. cyanobacterium 3 prevailed at the mid-to-up-glacier sites (S3–S5). This niche partitioning is likely driven by physical factors associated with altitude, specifically the duration of bare-ice exposure. The downstream sites (S1–S2) experience the earliest snow disappearance and the longest continuous melt season, allowing for the prolonged accumulation and structural stabilization of ice-surface microbial communities (Hodson et al., 2010; Uetake et al., 2010). The dominance of Osc. cyanobacterium 2 at these lower-elevation sites suggests an association with more developed, stable cryoconite habitats characterized by cumulative dust aggregation. In contrast, the mid-to-up glacier sites (S3–S5) encounter a much shorter exposure window. The dominance of Osc. cyanobacterium 3 in these upper areas, including a sharp increase in detectable biomass (exceeding 470 <inline-formula><mml:math id="M137" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">L</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">m</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">2</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>) during P4, indicates that this taxon is a potential pioneer microorganism well-adapted to recently exposed ice surfaces (Ortiz-Álvarez et al., 2018; Bradley et al., 2023). This apparent biomass spike was likely driven by the removal of the seasonal snow cover, which newly uncovered the underlying resident cyanobacterial cells on the ice surface. Alternatively, its prevalence at higher elevations may reflect a greater physiological tolerance to recurrent freeze–thaw cycles.</p>
      <p id="d2e2644">This altitudinal segregation implies that the cyanobacterial community is a strategically partitioned system rather than a monolithic assemblage. For instance, different cyanobacterial taxa may contribute uniquely to cryoconite granule formation (Chen et al., 2025) and vary in their capacities for light utilization and nutrient cycling (Murakami et al., 2022). The presence of multiple dominant taxa with distinct spatio-temporal peaks ensures that the glacier surface maintains high biological biomass across a wide range of environmental conditions – from stable lower reaches to dynamic, highly disturbed upper reaches. Consequently, the functional diversity within the Oscillatoriaceae contributes to the persistence and expansive spatial extent of biological darkening across the entire ablation zone.</p>
      <p id="d2e2647">Unlike the ephemeral algal blooms on Arctic glaciers (Takeuchi, 2013), the biological impact on Urumqi Glacier No. 1 is stabilized by the formation and multi-year persistence of cryoconite granules driven by filamentous cyanobacteria. While polar glacier algae, such as <italic>Anancylonema nordenskiöldii</italic>, exhibit explosive seasonal growth dynamics (Stibal et al., 2017; Onuma et al., 2023), the cyanobacterial biomass on Urumqi Glacier No. 1 remained relatively constant throughout the melt season. This lack of a seasonal spike suggests a fundamentally distinct ecological strategy: while polar ice algae thrive through opportunistic, rapid seasonal blooms, the cyanobacteria here rely on the long-term retention of stable structural aggregates. These filamentous taxa produce extracellular polymeric substances (EPS) that trap mineral dust, forming dark, spherical granules (Musilova et al., 2016; Segawa et al., 2017) that can persist and grow over multiple melt seasons (Takeuchi et al., 2010). This prolonged development facilitates the accumulation of refractory humic substances, significantly enhancing the cumulative light-absorbing capacity of the aggregates (Takeuchi, 2002).</p>
      <p id="d2e2654">Crucially, the spatial manifestation of these aggregates differs fundamentally from polar systems. On polar ice sheets, cryoconite is often concentrated within localized cryoconite holes, rendering its sheet-wide albedo impact secondary to vast, distributed ice algal blooms (Cook et al., 2020). Conversely, the bare-ice surface of Urumqi Glacier No. 1 is extensively covered by dispersed cryoconite rather than discrete holes (Takeuchi and Li, 2008). The high spatial occupancy of this dispersed material, combined with its structural stability provided by the cyanobacterial matrix, helps retain these dark, humic-rich aggregates on the ice surface even during minor scouring events. While literature suggests that consolidated organic-inorganic aggregates exert localized radiative impacts (Cook et al., 2016; Hotaling et al., 2021), the proliferation and retention of these filamentous taxa represents a key biological factor, interacting alongside heavy mineral dust loading, that drives the persistent and cumulative surface darkening observed on this Central Asian glacier.</p>
</sec>
<sec id="Ch1.S4.SS4">
  <label>4.4</label><title>Environmental drivers: Nitrogen limitation and mineral-derived ions</title>
      <p id="d2e2665">The distinct community compositions on snow and ice surfaces suggest different environmental controls. We found significant negative correlations between inorganic nitrogen concentrations (<inline-formula><mml:math id="M138" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NO</mml:mi><mml:mn mathvariant="normal">3</mml:mn><mml:mo>-</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M139" display="inline"><mml:mrow class="chem"><mml:msubsup><mml:mi mathvariant="normal">NH</mml:mi><mml:mn mathvariant="normal">4</mml:mn><mml:mo>+</mml:mo></mml:msubsup></mml:mrow></mml:math></inline-formula>) and the relative abundance of dominant filamentous cyanobacteria (Oscillatoriaceae) (<inline-formula><mml:math id="M140" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>; Fig. 7). This statistical trend indicates a close coupling between inorganic nitrogen availability and cyanobacterial proliferation on the ice surface. Rather than implying a one-way causal advantage, this negative correlation may reflect the progressive biological drawdown of available nutrients by the high-biomass cyanobacterial mats during their active growth phase, a process supported by their metabolic pathways for efficient nutrient utilization and recycling within the cryoconite micro-habitats (Segawa et al., 2014, 2020; Murakami et al., 2022).</p>

      <fig id="F7" specific-use="star"><label>Figure 7</label><caption><p id="d2e2708">Correlation between major ion concentration and bio-volume of each algal and cyanobacterial taxa.</p></caption>
          <graphic xlink:href="https://tc.copernicus.org/articles/20/4957/2026/tc-20-4957-2026-f07.png"/>

        </fig>

      <p id="d2e2717">Furthermore, although no significant relationship was observed between Oscillatoriaceae biomass and the mineral fractions during P5, potentially due to the limited sample size, Oscillatoriaceae biomass was positively correlated with mineral-derived ions (<inline-formula><mml:math id="M141" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Ca</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M142" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, and <inline-formula><mml:math id="M143" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">K</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:mrow></mml:math></inline-formula>, <inline-formula><mml:math id="M144" display="inline"><mml:mrow><mml:mi>p</mml:mi><mml:mo>&lt;</mml:mo><mml:mn mathvariant="normal">0.05</mml:mn></mml:mrow></mml:math></inline-formula>, Fig. 7). In Central Asian glacier systems, intense atmospheric dust deposition and subsequent lithogenic mineral weathering strongly govern the meltwater chemistry, making these dissolved cations reliable indicators of mineral influence (Li et al., 2006; Wu et al., 2012). The concentrations of these ions on Urumqi Glacier No. 1 are substantially higher than those reported for Arctic glaciers, such as those in Svalbard, where mineral-derived ion concentrations are significantly lower due to limited dust input (Takeuchi et al., 2019). While glacier algae (such as <italic>Ancylonema</italic> spp., formerly <italic>Ancylonema</italic>) are commonly reported to dominate the low-mineral environments of Svalbard glaciers (Stibal et al., 2017), the high mineral availability on Urumqi Glacier No. 1 provides a more suitable substrate and nutrient base for the proliferation of filamentous cyanobacteria and the subsequent development of cryoconite granules. This stark contrast in geochemical conditions explains why the primary biological drivers of albedo reduction differ so fundamentally between Central Asian and Arctic glacial systems – where the former relies on dust-mediated cyanobacterial aggregation (Segawa and Takeuchi, 2010; Takeuchi and Li, 2008) and the latter is driven by widespread blooms of specialized eukaryotic ice algae (Williamson et al., 2018; Cook et al., 2020).</p>
      <p id="d2e2779">This relationship highlights the critical importance of mineral availability for cyanobacterial colonization and granule formation. Our results mirror observations from the Greenland Ice Sheet, where phosphorus and mineral availability are key drivers of cyanobacterial growth (Uetake et al., 2019), but this effect is likely amplified on Urumqi Glacier No. 1 due to the extreme dust deposition characteristic of Central Asian mountains. In contrast, algal taxa showed no such correlations, suggesting their distribution may be driven by stochastic colonization or micro-scale physical factors like meltwater flow rather than macro-scale chemical parameters (Stibal et al., 2012a).</p>
</sec>
<sec id="Ch1.S4.SS5">
  <label>4.5</label><title>Ecological Implications and comparison with Arctic glaciers</title>
      <p id="d2e2791">One of the most significant ecological findings of this study is the complete absence of glacier algae, such as <italic>Ancylonema</italic> spp., which are the primary drivers of ice darkening on Arctic glaciers (e.g., Alaska, Svalbard) (Takeuchi, 2013; Takeuchi et al., 2019). In polar regions, these Zygnematalean algae bloom on the ice surface, producing dark purple pigments that significantly reduce albedo (Williamson et al., 2018; Remias et al., 2012). However, on Urumqi Glacier No. 1, this niche is predominantly occupied by a stable, cyanobacteria-dominated community.</p>
      <p id="d2e2797">The absence of <italic>Ancylonema</italic> and the corresponding dominance of filamentous cyanobacteria (Oscillatoriaceae) are likely attributable to the unique geochemical and physical environment of Central Asia. Takeuchi et al. (2019) demonstrated that Arctic glaciers in Svalbard are characterized by extremely low mineral ion concentrations, a condition that appears to favor the proliferation of free-living glacier algae. In contrast, the high dust flux on Urumqi Glacier No. 1 provides an abundance of mineral cations, resulting in substantially elevated ionic concentrations. For example, mean <inline-formula><mml:math id="M145" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> and <inline-formula><mml:math id="M146" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Ca</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula> concentrations on Urumqi Glacier No. 1 are approximately 13 and 59 times higher, respectively, than those reported for Svalbard (<inline-formula><mml:math id="M147" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Mg</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>: 20.6 vs. 1.6 <inline-formula><mml:math id="M148" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace linebreak="nobreak" width="0.125em"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>; <inline-formula><mml:math id="M149" display="inline"><mml:mrow class="chem"><mml:msup><mml:mi mathvariant="normal">Ca</mml:mi><mml:mrow><mml:mn mathvariant="normal">2</mml:mn><mml:mo>+</mml:mo></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>: 125.5 vs. 2.1 <inline-formula><mml:math id="M150" display="inline"><mml:mrow class="unit"><mml:mi mathvariant="normal">µ</mml:mi><mml:mi mathvariant="normal">Eq</mml:mi><mml:mspace width="0.125em" linebreak="nobreak"/><mml:msup><mml:mi mathvariant="normal">L</mml:mi><mml:mrow><mml:mo>-</mml:mo><mml:mn mathvariant="normal">1</mml:mn></mml:mrow></mml:msup></mml:mrow></mml:math></inline-formula>, Takeuchi et al., 2019). These elevated mineral inputs maintain a higher pH on the ice surface. The high influx of carbonate-rich mineral dust from surrounding arid regions acts as a powerful geochemical buffer, maintaining the meltwater pH in a neutral-to-alkaline range (typically 7.5–8.5; Li et al., 2007; Wu et al., 2012). Such alkaline, mineral-rich conditions may be physiologically inhibitory to Anancylonema (formerly Ancylonema), which typically thrives in the more acidic, ultra-oligotrophic environments characteristic of polar ice (Remias et al., 2012; McCutcheon et al., 2021).</p>
      <p id="d2e2898">Furthermore, the physical presence of massive mineral dust promotes the formation of cryoconite granules. As revealed by Segawa and Takeuchi (2010) on Qiyi Glacier and further elucidated by Chen et al. (2025) on Urumqi Glacier No. 1, filamentous cyanobacteria act as “ecosystem engineers,” trapping mineral particles to form stable, spherical aggregates. This process may physically exclude glacier algae by reducing the availability of “clean” ice surfaces required for their colonization.</p>
      <p id="d2e2901">These results suggest that biological darkening on Central Asian glaciers may differ from the algal bloom, dominated patterns commonly reported for Arctic glaciers. While Arctic darkening is often ephemeral and sensitive to seasonal snowmelt timing, the darkening on Urumqi Glacier No. 1 is more persistent due to the structural stability of cyanobacterial cryoconite. Therefore, applying Arctic-based bio-albedo models to Central Asian glaciers may lead to significant errors, highlighting the need for region-specific models that account for high mineral loading and its role in shaping microbial community structures.</p>
</sec>
</sec>
<sec id="Ch1.S5" sec-type="conclusions">
  <label>5</label><title>Conclusion</title>
      <p id="d2e2914">This study characterized the spatio-temporal dynamics of phototrophic communities on Urumqi Glacier No. 1, revealing an ecological structure fundamentally distinct from those of better-studied polar glacial systems. The primary finding of this research is the clear biological succession driven by the seasonal transition of the glacier surface. As the snowpack recedes, the community shifts from the dominance of snow algae (<italic>Chloromonadinia</italic> species) to a massive proliferation of filamentous cyanobacteria (Oscillatoriaceae) on the exposed bare ice. This transition is marked by a significant increase in total biomass and the establishment of a stable microbial community that persists throughout the melt season.</p>
      <p id="d2e2920">Crucially, this study highlights the absence of eukaryotic glacier algae such as <italic>Anancylonema</italic> spp., which are the primary drivers of ice darkening on Arctic glaciers. Instead, the biological darkening process on Urumqi Glacier No. 1 is governed by the extensive development of these filamentous cyanobacterial mats interacting with abundant mineral particles. Our results demonstrate that the proliferation of dominant filamentous cyanobacteria is closely linked to high concentrations of mineral-derived ions and low inorganic nitrogen levels. This geochemical environment, shaped by high dust input from surrounding arid regions, appears to provide a specialized niche that favors cyanobacterial colonization and the structural development of cryoconite granules over the growth of eukaryotic glacier algae. Furthermore, we identified an altitudinal niche partitioning within the Oscillatoriaceae, where different taxa (e.g., Osc. cyanobacterium 2 and 3) dominate based on the altitudinal gradient and the corresponding duration of bare-ice exposure. This functional diversity ensures that a high biological biomass is maintained across the entire ablation zone.</p>
      <p id="d2e2926">The ecological implications of these findings are essential for predicting the future of alpine glaciers in a changing climate. Unlike the ephemeral algal blooms observed in Arctic regions, the darkening on Urumqi Glacier No. 1 is driven by structurally stable cryoconite granules that potentially persist across melt seasons. This prolonged development facilitates the accumulation of refractory humic substances, creating a more constant and resilient bio-albedo feedback pathway. Under projected warming scenarios, including extended melt seasons and increased dust deposition, the expansion of these cyanobacterial communities may further accelerate glacier mass loss. Therefore, it is imperative to integrate region-specific microbial dynamics, characterized by the absence of glacier algae and the dominance of mineral-buffered, long-lived cyanobacterial aggregates, into global glacier melt models to improve the accuracy of water resource projections in Central Asia.</p>
</sec>

      
      </body>
    <back><notes notes-type="dataavailability"><title>Data availability</title>

      <p id="d2e2933">The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request. The datasets are currently not deposited in a public repository due to institutional data management policies of the affiliated university. The corresponding author is willing to provide access to the data for research purposes upon reasonable request and following confirmation of compliance with institutional requirements.</p>
  </notes><app-group>
        <supplementary-material position="anchor"><p id="d2e2936">The supplement related to this article is available online at <inline-supplementary-material xlink:href="https://doi.org/10.5194/tc-20-4957-2026-supplement" xlink:title="zip">https://doi.org/10.5194/tc-20-4957-2026-supplement</inline-supplementary-material>.</p></supplementary-material>
        </app-group><notes notes-type="authorcontribution"><title>Author contributions</title>

      <p id="d2e2945">YC and NT designed the study. YC and NT wrote and revised the manuscript with supports of XH and WZ. ST collected samples and quantified biomass of algae and cyanobacteria. NT measured ion concentration. YC and SL statistically analyzed data and draw figures. ZL organized the field investigation.</p>
  </notes><notes notes-type="competinginterests"><title>Competing interests</title>

      <p id="d2e2951">The contact author has declared that none of the authors has any competing interests.</p>
  </notes><notes notes-type="disclaimer"><title>Disclaimer</title>

      <p id="d2e2957">Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. The authors bear the ultimate responsibility for providing appropriate place names. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.</p>
  </notes><notes notes-type="sistatement"><title>Special issue statement</title>

      <p id="d2e2963">This article is part of the special issue “Cryospheric ecosystems: climate feedback loops, threatened ecosystems, and consequences of climate change”. It is not associated with a conference.</p>
  </notes><ack><title>Acknowledgements</title><p id="d2e2969">We gratefully acknowledge the invaluable support provided by the members of the Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China, during the fieldwork. We would also like to show our gratitude to Dr. Zanpin Xin for meteorological data support. We sincerely thank the Editor and the two anonymous reviewers for their constructive and valuable comments, which have helped us improve the manuscript.</p></ack><notes notes-type="financialsupport"><title>Financial support</title>

      <p id="d2e2974">This study was financially supported by the JSPS KAKENHI (grant nos. 25K22868, 24H00260, 22H03731, 21H0457, and 20H00196) and Young Scientists Fund of the National Natural Science Foundation of China (grant nos. 42306268 and 42201056).</p>
  </notes><notes notes-type="reviewstatement"><title>Review statement</title>

      <p id="d2e2980">This paper was edited by Elizabeth Bagshaw and reviewed by two anonymous referees.</p>
  </notes><ref-list>
    <title>References</title>

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