Habitat heterogeneity stimulates regeneration of bryophytes and vascular plants on disturbed minerotrophic peatlands
Bibliographic record
Abstract
Wooded rich fens (WRF), characterized by high variation in surface topography and numerous plant species organized along microtopographic gradients, are abundant in continental western Canada. In regions where in situ oil sands exploration (OSE) prevails, however, winter operations eliminate the surface vegetation and mechanically flatten the exposed peat. This results in saturated or flooded soils during the growing season and eliminates plant species dependent on naturally elevated microhabitats, with implications for peatland recovery. In northeastern Alberta, we redeveloped hummock topography on replicate WRF after OSE by extracting blocks of frozen peat from peatland surfaces in the winter. Peat mounds and adjacent unmounded flattened areas were left to regenerate naturally and were sampled four to five summers later. Mounds facilitated the colonization of many peatland plants not adapted to waterlogged soils. For bryophytes, mean richness and diversity of liverworts, Sphagnum, and true mosses were higher in mounded plots than in unmounded plots. For vascular plants, woody plants (trees and shrubs) had higher richness, cover, and diversity (trees only) in mounded plots. Peat mounding may be effective for stimulating vegetation development on OSE-degraded WRF. All mounds, however, will require lateral expansion by hummock-forming mosses to provide the habitat volume required for development of large woody plants.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".