Growth Response of Aspen and Alder to Fresh and Stockpiled Reclamation Soils
Bibliographic record
Abstract
Soil stockpiling is a common reclamation practice used in oil sands mining in the boreal forest region of Canada to conserve soil resources; but stockpiling may have detrimental effects on soil quality and plant growth. We examined growth response of trembling aspen (Populus tremuloides Michx.), a fast-growing early successional tree, and green alder (Alnus viridis (Chaix) DC. ssp crispa (Ait.) Turrill), a nitrogen-fixing shrub, to stockpiling and fertilization treatments on two reclamation soils (forest floor mineral mix (FFMM) and peat mineral mix (PMM)). Aspen and alder seeds were planted and their growth monitored for four months in the greenhouse. We found that unfertilized stockpiled FFMM supported significantly higher aspen and alder aboveground biomass than the other fresh and stockpiled soils. Phosphorus and potassium supply rates were highest in stockpiled FFMM and were positively correlated with aboveground plant biomass. There was no significant difference in aspen and alder aboveground biomasses between unfertilized fresh FFMM and PMM soils. Aspen grown in combination with nitrogen-fixing alder did not experience competition or facilitation except on fresh PMM, where aspen height declined. Fertilization increased both aspen and alder growth and eliminated differences in growth between soil types and stockpiling treatments. Our study showed that individual soil properties are more important for revegetation purposes than type of soil or stockpiling treatment.
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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".