Nutrient distribution in sandy soils along a forest productivity gradient in the Athabasca Oil Sands Region of Alberta, Canada
Bibliographic record
Abstract
Brunisolic soils developed on sandy deposits comprise a significant portion of the land disturbed by surface mining in the Athabasca Oil Sands Region. These soils support forest communities ranging from nutrient limited jack pine to more productive aspen stands. The objective of this study was to determine if and how the physical properties of these sandy soils influence the accumulation and distribution of soil nutrients. Sixteen sites, selected to capture the natural range in forest productivity of the area, were characterized to assess particle size distribution, total and available nutrient stocks in forest floors, total C and N, and extractable nutrients in B horizons. Under jack pine, relatively small decreases in sand content of the upper soil profiles, from 97% to 88%, were associated with greater total nutrient stocks and lower C/N ratios in the forest floors. In soils under aspen, forest floor nutrient stocks related most strongly with texture of the B horizons, with finer B horizons (from 94% to 78% sand) leading to larger forest floor nutrient stocks. These results indicate that textural characteristics play an important role in nutrient cycling of these sandy soils and should be a primary focus during their reclamation.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".