Peat deformation and biogenic gas bubbles control seasonal variations in peat hydraulic conductivity
Bibliographic record
Abstract
Abstract The hydraulic conductivity (K) of peat beneath the water table varies over short (annual) periods. Biogenic gas bubbles block pores and reduce K, and seasonal changes in the water table position cause peat deformation, altering peat pore size distribution. Although it has been hypothesized that both processes reduce K during warm dry summer conditions, temporal variations in K under field conditions have been explained previously by peat volume changes (strain) alone. We determine the effect of both controls on K by monitoring changes in gas content (Δγ), strain and K within a poor fen. Over the growing season, K decreased by an order of magnitude. In the near‐surface peat (0.3–0.7 m), this reduction is more strongly correlated with Δγ, providing the first field‐based evidence that biogenic gas bubbles reduce K. In the deeper peat (0.7–1.3 m), K is correlated principally with strain. However, causality is uncertain because of multicollinearity between strain and Δγ. To mitigate for multicollinearity, we took advantage of a peatland drainage experiment where the water table was artificially dropped at the beginning of the growing season, reducing correlations between strain and Δγ. Δγ remained the primary cause of K variations just beneath the water table at a depth of 0.5–0.7 m, although further down through the peat profile (0.7–1.2 m) changes in K were controlled by strain. We suggest that the larger pore structure of the poorly decomposed peat just below the water table is impacted less by volume changes than that of the more decomposed peat at depth. However, within this poorly decomposed peat, K is reduced by the high gas contents that result from higher rates of methane production. Copyright © 2012 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 | 0.000 | 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".