Vegetation patterns and biodiversity of peatland plant communities surrounding mid-boreal wetland ponds in Alberta, Canada
Bibliographic record
Abstract
Peatland plant communities surrounding small (<200 ha) boreal ponds were characterized by indicator species, water and peat chemistry, and diversity. Peatlandpond complexes are common in boreal Alberta and are found in three different landforms (clay-till plain, outwash plain, and moraine). Pond area and perimeter were larger in the clay-till plain than in other landforms, although not significantly different. Across the three landforms, cluster analysis detected five peatland communities: marshes, wet open fens, dry open fens, treed fens, and bogs. The zonation pattern of communities surrounding the ponds varied at all sites, and there was no typical pattern, except that marshes were always found closest to water. Based on the bryophyte species, most communities are considered moderate-rich fens. Nonmetric multidimensional scaling indicated communities fell along a wet-to-dry gradient and a bare-to-vegetated gradient. Water depth and temperature, peat depth, and peat C/N ratios differed between open and treed peatland communities, and pH was similar in all communities. Alpha and gamma diversity was highest in the treed fen and lowest in the marsh community in both total species and bryophyte species. The total number of plant species, some of which are considered rare, found in all communities was 139.Key words: marsh, fen, bog, classification, vegetation ecology, diversity.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".