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Overgeneralization and a lack of baseline data for microorganisms in high-latitude environments have restricted the understanding of the microbial response to climate change, which is needed to establish Antarctic conservation frameworks. To bridge this gap, we examined over 17,000 sequence variants of bacteria and microeukarya across the hyperarid Vestfold Hills and Windmill Islands regions of eastern Antarctica. Using an extended gradient forest model, we quantified multispecies response to variations along 79 edaphic gradients to explore the effects of change and wind-driven dispersal on community dynamics under projected warming trends. We also analyzed a second set of soil community data from the Windmill Islands to test our predictions of major environmental tipping points. Soil moisture was the most robust predictor for shaping the regional soil microbiome; the highest rates of compositional turnover occurred at 10-12% soil moisture threshold for photoautotrophs, such as Cyanobacteria, Chlorophyta, and Ochrophyta. Dust profiles revealed a high dispersal propensity for Chlamydomonas, a microalga, and higher biomass was detected at trafficked research stations. This could signal the potential for algal blooms and increased nonendemic species dispersal as human activities increase in the region. Predicted increases in moisture availability on the Windmill Islands were accompanied by high photoautotroph abundances. Abundances of rare oligotrophic taxa, such as Eremiobacterota and Candidatus Dormibacterota, which play a crucial role in atmospheric chemosynthesis, declined over time. That photosynthetic taxa increased as soil moisture increased under a warming scenario suggests the potential for competition between primary production strategies and thus a more biotically driven ecosystem should the climate become milder. Better understanding of environmental triggers will aid conservation efforts, and it is crucial that long-term monitoring of our study sites be established for the protection of Antarctic desert ecosystems. Furthermore, the successful implementation of an improved gradient forest model presents an exciting opportunity to broaden its use on microbial systems globally.
Zhang et al. (Mon,) studied this question.