Trembling aspen seedling establishment, growth and response to fertilization on contrasting soils used in oil sands reclamation
Bibliographic record
Abstract
Pinno, B. D., Landhäusser, S. M., MacKenzie, M. D., Quideau, S. A. and Chow, P. S. 2012. Trembling aspen seedling establishment, growth and response to fertilization on contrasting soils used in oil sands reclamation. Can. J. Soil Sci. 92: 143–151. Trembling aspen (Populus tremuloides) is an important tree species for land reclamation. This study determined trembling aspen germination, establishment, initial growth and response to fertilizer on contrasting oil sands reclamation soils. In a greenhouse, eight soils varying in total nitrogen and available phosphorus were treated with no fertilizer (control), phosphorus and potassium (PK), nitrogen (N) and all three (NPK). Soil had the greatest impact on aspen growth when no fertilizer was applied with the best growth occurring on organic-mineral material soils where growth was positively correlated with extractable and foliar potassium but not to nitrogen or phosphorus. With PK and N fertilizer, growth increases were positively correlated with foliar phosphorus concentrations of the corresponding controls. NPK fertilizer caused greater growth, bud set and root:leaf mass ratio compared with PK or N fertilizer. Soil type had little impact on germination and establishment, indicating natural aspen seedlings can potentially regenerate on all of these soils. In oil sands mining reclamation where these soils are used as surface materials, organic-mineral mixes had the greatest potential without fertilizer. With fertilizer, NPK provided maximum growth and developmental benefits.
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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) | 0.001 | 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".