Soil properties following borrow pit reclamation with insufficient topsoil amended with peat and biochar
Bibliographic record
Abstract
Abstract Disturbed sites, such as borrow pits and oil and natural gas well sites, require reclamation to restore and sustain levels of productivity similar to those prior to the disturbance. However, salvaged topsoil at many sites is often insufficient to meet the 80% topsoil replacement depth (TRD80) required for successful reclamation in western Canada. This 5‐year study evaluated soil responses to 50% topsoil replacement depth without organic amendment (TRD50) or amended with either peat (PTRD50) or biochar (BTRD50), relative to the TRD80 treatment (Control), following borrow pit reclamation at a disturbed boreal site near Cold Lake, Alberta, Canada. Amendments were applied once at rates calculated to raise the soil organic carbon (SOC) content in the TRD50 soil to a level equal to that in the TRD80 treatment. Results showed a 143%, 87%, and 116% increase in total Kjeldahl nitrogen concentration in the PTRD50 relative to the TRD80, TRD50, and BTRD50 treatments, respectively, while soil potassium (K) concentration was significantly greater for BTRD50 than PTRD50. Peat and biochar significantly increased SOC concentrations by 83% and 88%, respectively, relative to the mean of TRD80 and TRD50 treatments. Our results show that peat and biochar can improve soil properties of disturbed boreal sites reclaimed with insufficient salvaged topsoil to a level suitable for successful reclamation. This has important implications on the reclamation of a multitude of disturbed sites, in Canada and globally, that have insufficient volumes of salvaged topsoil needed for successful 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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".