Migration of Paraburkholderia terrae BS001 Along Old Fungal Hyphae in Soil at Various pH Levels
Bibliographic record
Abstract
The movement of bacterial cells along with fungal hyphae in soil (the mycosphere) has been reported in several previous studies. However, how local soil conditions affect bacterial migration direction in the mycosphere has not been extensively studied. Here, we investigated the influence of two soil parameters, pH and soil moisture content, on the migration, and survival, of Paraburkholderia terrae BS001 in the mycosphere of Lyophyllum sp. strain Karsten in microcosms containing a loamy sand soil. The data showed that bacterial movement along the hyphal networks took place in both the "forward" and the "backward" directions. Low soil pH strongly restricted bacterial survival, as well as dispersal in both directions, in the mycosphere. The backward movement was weakly correlated with the amount of fungal tissue formed in the old mycelial network. The initial soil moisture content, set at 12 versus 17% (corresponding to 42 and 60% of the soil water holding capacity), also significantly affected the bacterial dispersal along the fungal hyphae. Overall, the presence of fungal hyphae was found to increase the soil pH (under conditions of acidity), which possibly exerted protective effects on the bacterial cells. Finally, we provide a refined model that describes the bacterial migration patterns with fungal hyphae based on the new findings in this study.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".