Distinct phototrophic community structure on a Central Asian glacier: predominance of filamentous cyanobacteria and absence of glacier algae ( Ancylonema spp.)

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 Chloromonadinia 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 Ancylonema 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.