Sustaining the growth of Pinaceae trees under nutrient-limited edaphic conditions via plant-beneficial bacteria
Bibliographic record
Abstract
Lodgepole pine, a prominent Pinaceae tree species native to western North America, is well-known for its ability to thrive in highly disturbed and degraded areas. One such area is the Sub-Boreal Pine-Spruce xeric-cold (SBPSxc) region in British Columbia, Canada, which is characterized by weakly-developed, parched soils that lack an organic forest floor and essential plant-available nutrients. We hypothesized that plant growth-promoting bacteria could play a significant role in sustaining the growth of lodgepole pine trees in the SBPSxc region. Testing this hypothesis, we evaluated plant growth-promoting abilities of six endophytic bacterial strains previously isolated from lodgepole pine trees growing in this region. These bacterial strains significantly enhanced the length and biomass of their natural host (lodgepole pine) as well as a foreign host (hybrid white spruce) in a 540-day long greenhouse trial. This growth stimulation could be linked to the diverse plant growth-promoting (PGP) abilities detected in these strains using in vitro assays for inorganic/organic phosphate-solubilization, siderophore production IAA production, ACC deaminase activity, lytic enzymes (chitinase, β-1,3-glucanase, protease, and cellulase) activity, ammonia production and catalase activity. ACC deaminase activity was also detected in vivo for all strains using ethylene-sensitive plants-canola and tomato. Notably, strains belonging to the Burkholderiaceae family (HP-S1r, LP-R1r and LP-R2r) showed the greatest potential in all PGP assays and enhanced pine and spruce seedling length and biomass by up to 1.5-fold and 4-fold, respectively. Therefore, such bacterial strains with multifarious PGP abilities could be crucial for survival and growth of lodgepole pine trees in the SBPSxc region and could potentially be utilized as bioinoculant for Pinaceae trees in highly disturbed and nutrient-poor ecosystems.
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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) | 0.000 | 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".