Analysis of microbial communities in natural halite springs reveals a domain‐dependent relationship of species diversity to osmotic stress
Bibliographic record
Abstract
Microbial species diversity may peak at certain optimal environmental conditions and decrease toward more extreme conditions. Indeed, bell-shaped relationships of species diversity against pH and temperature have been demonstrated, but diversity patterns across other environmental conditions are less well reported. In this study, we investigated the impact of salinity on the diversity of microorganisms from all three domains in a large set of natural springs with salinities ranging from freshwater to halite saturated. Habitat salinity was found to be linearly and inversely related to diversity of all three domains. The relationship was strongest in the bacteria, where salinity explained up to 44% of the variation in different diversity metrics (OTUs, Shannon index, and Phylogenetic Diversity). However, the relationship was weaker for Eukarya and Archaea. The known salt-in strategist Archaea of the Halobacteriaceae even showed the opposite trend, with increasing diversity at higher salinity. We propose that high energetic requirements constrain species diversity at high salinity but that the diversity of taxa with energetically less expensive osmotolerance strategies is less affected. Declining diversity with increasing osmotic stress may be a general rule for microbes as well as plants and animals, but the strength of this relationship varies greatly across microbial taxa.
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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 | 0.001 | 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".