Topsoil replacement depth and organic amendment effects on plant nutrient uptake from reclaimed natural gas wellsites
Bibliographic record
Abstract
Sustained plant nutrient a vailability on reclaimed wellsites is critical to the successful restoration of crop productivity. This study evaluated topsoil replacement depth (TRD) (0, 50, 100, and 150% of mandatory TRD) and organic amendment [beef cattle feedlot manure, compost derived from straw-bedded cattle feedlot manure, wheat (Triticum aestivumL.) straw, alfalfa (Medicago sativaL.) hay, and unamended control] effects on nutrient uptake by a wheat crop at three abandoned gas wellsites in south-central Alberta. Grain N uptake increased by 0.055 kg ha-1 for each percent increase in TRD, reflecting the corresponding linear increase in grain N concentration. Low carbon to nitrogen (C:N) ratio amendments, particularly compost and alfalfa, were the most effective for improving grain N concentration and uptake. Conversely, N concentration and uptake were lowest for the high C:N (53:1) wheat straw amendment. Reclamation programs should, therefore, consider incorporation of the low C:N alfalfa or compost in order to safeguard against N deficiency in the first 1–2 yr following reclamation. Our results also show that high P amendments, such as manure and compost, are better choices for improving P uptake by spring wheat. These results emphasize the importance of topsoil replacement and amendment quality (C:N ratio and P concentration) in ensuring adequate N and P supply in the 1–2 yr following reclamation. Based on this, compost appears to be the best single amendment for ensuring enhanced uptake of both N and P on reclaimed wellsites in the short term. Key words: Topsoil replacement; organic amendments; reclamation; nitrogen; phosphorus
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".