Biogeography of soda lake microbiome and uneven cross-continent transition rates
Bibliographic record
Abstract
Microbial dark matter in soda lakes has been increasingly illuminated, however, much remains unknown about microbial biogeography at the global scale and underlying mechanisms. To study microbial biogeography and dispersal patterns, we analyzed 51 soda lake metagenomes collected from key global regions, including 37 from the Kulunda Steppe in South Siberia, Mongolia, and the Cariboo Plateau in Canada, as well as 14 newly sequenced samples from the East African Rift Valley. We found that there were 575 widespread taxa such as the dominant archaeal Haloarchaeota and actinobacterial Nitriliruptor persistently inhabiting global soda lakes. We further identified 1,217 region-specific taxa, with Africa containing the highest proportion of geographical endemism (66.72%). Such effects of dispersal limitation on microbial assembly of global soda lakes were supported by the significant distance-decay relationships for taxonomic and functional composition, and genomic similarity. For example, microbial genomic divergence was closely associated with their geographical distance, showing that both inter- and intraspecies genome similarities decayed with distance. This concurs with the uneven dispersal history among continental microbiomes, indicated by the at least one order of magnitude lower transition rates between Africa and other continents than between Asia and North America. Our results revealed that the global biogeography of soda lake microbial communities across three continents and their distinct transition history between continents. These findings highlight the critical role of microbial evolutionary history associated with dispersal limitation in shaping their geographical distribution in extreme environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".