Soil and plant response to wellsite rehabilitation on native prairie in southeastern Alberta, Canada
Bibliographic record
Abstract
Rehabilitation of disturbed native prairie is a challenge facing many in the petroleum industry, with implications for prairie ecology and productivity. The purpose of this research was to examine the relative influence of four rehabilitation strategies on biogeochemical processes (i.e., nitrogen availability, plant uptake of nitrogen, biomass production, carbon allocation, and soil biological activity). Seven petroleum wellsites were selected on Chernozemic and Solonetzic soils in southeastern Alberta. Undisturbed native prairie was compared with four seeding treatments: not seeded, a low diversity seed mix commonly used by industry, a low diversity mix of species more typically dominant in native prairie, and a diverse seed mix. Flux of NO3− and NH4+were measured in situ using ion exchange membranes. Soil total C and N were lower and available N higher as a result of disturbance. In the seeded treatments, biomass production was higher and soil nitrogen flux was lower due to higher plant uptake than in the unseeded treatment. Higher initial N availability favoured species with rapid growth and colonization rates, particularly Agropyron dasystachyum [(Hook.) Scribn.] and Agropyron trachycaulum [(Link) Malte]. Seed mix composition and species attributes were deemed to have greater influence on N cycling and biomass production than seed mix diversity. Key words: Nitrogen cycling, plant competition, secondary succession, wheatgrass, biodiversity, prairie
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".