Temporal Trends of Ecosystem Development on Different Site Types in Reclaimed Boreal Forests
Bibliographic record
Abstract
Forest development after land reclamation in the oil sands mining region of northern Alberta, Canada was assessed using long-term monitoring plots from both reclaimed and natural forests. The metrics of ecosystem development analyzed included measures of plant community structure and composition and soil nutrient availability. Early seral reclamation plots were grouped by site type (dry and moist-rich) and age categories, and these were compared with mature natural forests. There were few significant differences in ecosystem metrics between reclamation site types, but natural stands showed numerous significant differences between site types. Over time, there were significant changes in most plant community metrics such as species richness and cover of plant community groups (e.g., forbs, shrubs, and non-native species), but these were still substantially different from mature forests 20 years after reclamation. Available soil nitrogen did not change over time or by reclamation site type but available soil phosphorus did, suggesting that phosphorus may be a more suitable indicator of ecosystem development. The significant temporal changes in these reclaimed ecosystems indicate that studies of ecosystem establishment and development on reclaimed areas should be conducted over the long-term, emphasizing the utility of monitoring using long-term plot networks.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".