The Influence of Peat Volume Change and Vegetation on the Hydrology of a Kettle-Hole Wetland in Southern Ontario, Canada
Bibliographic record
Abstract
Links between local hydrology and vegetation type exist in wetlands, yet it is unclear what role peat volume change plays in these interactions. We measured peat volume change and hydraulic conductivity (K field ) at three contrasting sites located on the quaking vegetation mat of a kettle-hole peatland in southern Ontario. The three sites had visibly different plant communities and were named, according to their dominant vegetation, Sedge ( Carex spp.), Typha ( Typha angustifolia ) and Carr ( Cornus stolonifera ). Peat was also collected for laboratory studies of peat volume change, vertical (K v ) and horizontal (K h ) hydraulic conductivity and the effect of compression on hydraulic conductivity (K c ). In the field, the water table rose throughout the study period, resulting in swelling of the peat. Peat volume change above the -100 cm layer was 11.2%, 6.0% and 3.8% at the Sedge, Typha, and Carr sites respectively. In laboratory samples, a falling water table caused compression of the peat below the structured surface mat, and relative peat volume change between the sites followed the same pattern as in the field. K field , K v and K h generally decreased with depth from ca. 10-2 to 10-6 cm s-1. In the surface layers (0 to -50cm) K trended Carr>Typha>Sedge, whereas the reverse trend was observed in deeper peat. Artificial compression affected K only in the uppermost layers (0 to -15cm). The decline in K c with compression also trended Sedge>Typha>Carr. Differences in peat volume change and K are probably related to differences in vegetation and soil structure, and may be important for maintaining suitable growing conditions within each community.
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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 | 0.001 |
| 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 | 0.000 | 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".