Long-term effects of inoculating lodgepole pine seedlings with plant growth-promoting bacteria originating from a disturbed gravel mining ecosystem
Bibliographic record
Abstract
Gravel mining is prevalent in forest landscapes across Canada, typically resulting in complete loss of vegetation and topsoil. Despite such extreme disturbance, lodgepole pine (Pinus contorta Dougl. var. latifolia Engelm.) trees are thriving at unreclaimed gravel pits located in central-interior British Columbia, possibly owing to, at least in part, the association of pine trees with their endophytic bacteria. To test this possibility, several bacterial strains were previously isolated from pine trees growing at these pits; of the strains isolated, 14 were identified as effective nitrogen fixers. In this study, we evaluated the inoculation effect of these 14 strains on lodgepole pine growth under nitrogen-poor conditions. Eighteen months after sowing and inoculation, each strain had colonized the rhizosphere and internal tissues of pine seedlings and had significantly enhanced their length (24%–65%) and biomass (100%–300%). Notably, three Pseudomonas strains increased pine seedling length by 1.6-fold and biomass by 4-fold. Most strains also demonstrated substantial potential to promote plant growth via phosphorus solubilization, siderophore production, 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity, indole-3-acetic acid production, lytic enzyme activity, and catalase activity. Our results suggest that such nitrogen-fixing bacteria could be sustaining pine growth on bare gravel, indicating a possible ecological association that may explain natural tree regeneration in such a disturbed ecosystem.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".