The effects of water table draw‐down (as a surrogate for climate change) on the hydrology of a fen peatland, Canada
Bibliographic record
Abstract
Abstract Hydrological response to climate change may alter the biogeochemical role that peatlands play in the global climate system, so an understanding of the nature and magnitude of this response is important. In 2002, the water table in a fen peatland near Quebec City was lowered by ∼20 cm (Experimental site), and hydrological response was measured compared to Control (no manipulation) and Drained (previously drained c. 1994) sites. Because of the draw‐down, the surface in the Experimental pool decreased 5, 15 and 20 cm in the ridge, lawn and mat, respectively, increasing bulk density by ∼60% in the Experimental lawn. Hydraulic conductivity ( K ) generally decreased with depth and from Control (25–125 cm) 10 −1 to 10 −5 cm s −1 to Experimental (25–125 cm) 10 −2 to 10 −7 cm s −1 and to Drained (25–75 cm) 10 −2 to 10 −6 cm s −1 . In similar topographic locations (ridge, lawn, mat), K trended Control > Experimental > Drained, usually by an order of magnitude at similar depths in similar topographic locations. Water table fluctuations in the Drained site averaged twice those of the Control site. The water table in the Control lawn remained at a stable depth relative to the surface (∼− 1 cm) because the lawn peat floats with changes in water table position. However, the Drained lawn peat was more rigid because of the denser degraded peat, forcing the water to fluctuate relative to the surface and further enhancing peat decay and densification. This provides a positive feedback loop that could intensify further peat degradation, changing the carbon cycling dynamics. Copyright © 2006 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".