Can Mulch and Fertilizer Alone Rehabilitate Surface-disturbed Subarctic Peatlands?
Bibliographic record
Abstract
Subarctic peatlands are increasingly faced with disturbances from resource extraction industries. Their rehabilitation is being required through government regulation, and backed by financial guarantees. A three-year field experiment was conducted to test a modification of existing peatland rehabilitation protocols on winter road clearances in subarctic peatlands of the Hudson Bay Lowland. The experiment was conducted on severely disturbed sections of winter roads with extensive cut hummocks. Sphagnum fragments were not spread on bare peat surfaces, contrary to existing protocols, because of the close proximity to propagules in vast and adjacent, undisturbed peatlands. Factorial combinations of microclimate amelioration (straw mulch) and phosphorus fertilization were applied, as in existing protocols. Rock phosphate fertilization and straw mulch did not increase the recolonization of Sphagnum nor of other bryophytes, lichens or vascular plants. After three years, Sphagnum remained almost absent and bare peat was colonized mostly by lichens and bryophytes typical of disturbed peat surfaces. The spreading of fragments on top of severely disturbed surface peats appears to be required in order to rehabilitate peatlands, even when extensive undisturbed peatlands are found nearby.
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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 | 0.001 | 0.001 |
| 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 | 0.000 | 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".