bioRxivMicrobiologyPreprint
Tracing boundaries in Eastern Antarctica: Multi-scale drivers of soil microbial communities across the hyperarid Vestfold Hills
E. Zhang, P. Czechowski, A. Terauds, S. Y. Wong, D. S. Chelliah, M. Raven, M. M. Tanaka, B. C. Ferrari
Abstract
Microorganisms are key to sustaining core ecosystem processes across terrestrial Antarctica but they are rarely considered in conservation frameworks. Whilst greater advocacy has been made towards the inclusion of microbial data in this context, there is still a need for better tools to quantify multispecies responses to environmental change. Here, we extend the scope of Gradient Forest modelling beyond macroorganisms and small datasets to the comprehensive polar soil microbiome encompassing >17, 000 sequence variants for bacteria, micro-eukarya and archaea throughout the hyperarid Vestfold Hills of Eastern Antarctica. Quantification of microbial diversity against 79 physiochemical variables revealed that whilst rank-order importance differed, predictors were broadly consistent between domains, with greatest sharing occurring between bacteria and micro-eukarya. Moisture was identified as the most robust predictor for shaping the regional soil microbiome, with highest compositional turnover or "splits" occurring within the 10 - 12 % moisture content range. Often the most responsive taxa were rarer lineages of bacteria and micro-eukarya with phototrophic and nutrient-cycling capacities such as Cyanobacteria (up to 61.81 % predictive capacity), Chlorophyta (62.17 %) and Ochrophyta (57.81 %). These taxa groups are thus at greater risk of biodiversity loss or gain to projected climate trajectories, which will inevitably disturb current ecosystem dynamics. Better understanding of these threshold tipping points will positively aid conservation efforts across Eastern Antarctica. Furthermore, the successful implementation of an improved Gradient Forest model also presents an exciting opportunity to broaden its use on microbial systems globally.
- assay: DNA methylation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: ecology & biodiversity
- approach: statistical model
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