Aridity drives global convergence of desert microbiomes and biogeochemical activities
Bibliographic record
Abstract
Deserts cover a third of the world's surface, supporting unique biomes and ecosystem services. Yet, we lack a comprehensive assessment of what defines and drives the microbial communities that dominate life in these regions. Here, we conducted a standardized field survey in contrasting cold, hot, and polar deserts across the seven continents, and observed geographically distant deserts share similar structure, function, and activities. Desert communities are dominated by genomically streamlined Actinobacteriota and Chloroflexota, and compared with non-desert soils, are significantly enriched with stress tolerance genes, mobile genetic elements, and antiviral strategies, revealing previously unknown ecological and evolutionary dynamics. Metabolically, these communities exhibit reduced capacity for carbohydrate and protein degradation, and instead are enriched for chemosynthetic carbon fixation, continuous energy harvesting using atmospheric trace gases and sunlight, and energy reserve biosynthesis. All sampled soils mediated respiration, trace gas oxidation, and carbon fixation, with detectable activity even in hyper-arid Atacama and Antarctic soils at the margins of life. Driver analyses identified aridity as the primary overriding driver of the microbial communities and biogeochemical activities. Collectively, these findings suggest that aridity selects for metabolically self-sufficient taxa capable of continuously meeting energy and carbon needs independently of vegetation-derived inputs, while enduring physicochemical stressors and potentially elevated viral pressure. These new insights are integral to forecast the future of soils amid increasing desertification.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".