Impact of Drainage Ditch Construction and Subsequent Use on a Treed Bog Adjacent to a Peat Harvesting Operation, Southwestern Manitoba, Canada
Bibliographic record
Abstract
Manitoba has the most peatland by provincial area of any province in Canada, and contributes ~13% of Canada’s horticultural peatland production. Peat harvesting requires the lowering of the water table; this water is usually channeled to a fluvial system (e.g., a river) but in some cased must be actively pumped. In the case of the South Julius bog in Manitoba, the pumped discharge was through a treed bog. The trees in the bog on one side of the drainage ditch were dead, but on the other side were alive. This study investigated possible hydrological causes by instrumenting three transects of wells that ran perpendicular to the drainage ditch and extended 20 and 50 m into the bog on the dead and live side, respectively. Average water tables on the live side were 15 cm lower than the dead side. The dead side water levels were similar to a natural fen located adjacent to the treed bog. Construction of the drainage ditch yielded a >20 cm high berm that ran alongside the live side, functionally isolating the live side from the surplus water in the drainage ditch, maintaining the lower and healthier water table treed bog vegetation requires. We recommend that future drainage ditches be constructed in such a way that berms on both sides are made, functionally creating a canal to the fen, where the excess water can be more easily dealt with by the fen vegetation adapted to wetter average conditions.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".