Dormancy dampens the microbial distance-decay relationship
Bibliographic record
Abstract
ABSTRACT Much of Earth’s biodiversity has the capacity to engage in dormancy whereby individuals enter a reversible state of reduced metabolic activity. By increasing resilience to unfavorable conditions, dormancy leads to the accumulation of “seed banks” that should diminish the influence of environmental filtering, while allowing passive dispersers to colonize new habitats. Although prevalent among single-celled organisms, evidence that dormancy influences patterns of microbial biodiversity and biogeography is lacking. We constructed geographical and environmental distance-decay relationships (DDRs) using 16S rRNA sequencing to characterize the total (DNA) and the active (RNA) bacterial communities in a regional survey of 49 forested ponds. As expected, the total community harbored greater diversity and exhibited weaker DDRs than the active portion of the community. These empirical observations were robust to different measures of community similarity and random resampling tests. Furthermore, findings from the field survey were reproduced by models that included aspects of dormancy along with the geographical coordinates and environmental characteristics of our study system. In addition to maintaining local diversity, our results support recent theoretical predictions that dormancy shapes geographical patterns of biodiversity.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".