Nitrogen transformation rates are affected by cover soil type but not coarse woody debris application in reclaimed oil sands soils
Bibliographic record
Abstract
Forest floor mineral soil mix (FMM) and peat mineral soil mix (PMM) are cover soils commonly used for reclamation of open‐pit oil sands mining disturbed land in northern Alberta, Canada; coarse woody debris (CWD) is another source of organic matter for land reclamation. We investigated net nitrogen (N) transformation rates inFMMandPMMcover soils near and away fromCWD4–6 years after oil sands reclamation. Monthly net nitrification and N mineralization rates varied over time; however, mean rates across the incubation periods and microbial biomass were greater (p< 0.05) inFMMthan inPMM. Net N mineralization rates were positively related to soil temperature (p< 0.001) and microbial biomass carbon (p= 0.045). Net N transformation rates and inorganic N concentrations were not affected byCWD; however, the greater15Nisotope ratio of ammonium nearCWDthan away fromCWDindicates thatCWDapplication increased both gross N mineralization/nitrification (causing N isotope fractionation) and gross N immobilization (no isotopic fractionation). Microbial biomass was greater nearCWDthan away fromCWD, indicating the greater potential for N immobilization nearCWD. We conclude that (1)CWDapplication affected soil microbial properties and would create spatial variability and diverse microsites and (2) cover soil type andCWDapplication had differential effects on net N transformation rates. Applying FMM with CWD for oil sands reclamation is recommended to increase N availability and microsites.
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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 | 0.000 |
| 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) | 0.000 | 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".