Archaeal abundance in relation to root and fungal exudation rates
Bibliographic record
Abstract
Archaea are ubiquitous in forest soils, but little is known about the factors regulating their abundance and distribution. Low molecular weight organic compounds represent an important energy source for archaea in marine environments, and it is reasonable to suspect that archaeal abundance is dependent on such compounds in soils as well, represented by, for example, plant and fungal exudates. To test this hypothesis, we designed a microcosm experiment in which we grew ponderosa pine, sitka spruce, and western hemlock in forest soil. Root and mycorrhizal exudation rates were estimated in a 13C pulse-chase experiment, and the number of archaeal and bacterial 16S rRNA genes was determined by qPCR. Archaeal abundance differed among plant species, and the number of archaeal 16S rRNA genes was generally lower in soil receiving high concentration of exudates. The mycorrhizal fungi of ponderosa pine seemed to favor archaea, while no such effect was found for mycorrhized sitka spruce or western hemlock. The low abundance of archaea in the proximity of roots and mycorrhiza may be a result of slow growth rates and poor competitive ability of archaea vs. bacteria and does not necessarily reflect a lack of heterotrophic abilities of the archaeal community.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".