Differential peat deformation, compressibility, and water storage between peatland microforms: Implications for ecosystem function and development
Bibliographic record
Abstract
Because peat is elastic, the daily to seasonal swelling and shrinking of the peat surface not only affects water storage but also alters peatland hydraulics and the biogeochemical and thermal properties of peat. Due to different botanical origins and degrees of decomposition, we hypothesized that different peatland microforms (ridges and lawns) display a large variation in peat deformation and compressibility. Here we examined the spatial variation of peat surface movement, peat strength, and volumetric water content at a low lawn (LL), upper lawn (UL), and ridge (R) along a 5 m transect in a peatland in Quebec, Canada. The average seasonal amplitude in peat surface level was 9, 6, and 2 cm at the LL, UL, and R sites, respectively. The surface layers in each of these sites were fairly rigid with the largest changes in peat thickness occurring between 20 and 60 cm depth in the peat profile. Compressibility varied among microforms but was not correlated to other properties within the layer in individual soil layers. However, when average profile compressibility was considered, it was significantly correlated to peat depth, von Post humification, distance to hollow, and peat strength. The total water storage by dilation below the water table was about the same as the water deficit (precipitation minus evapotranspiration) for LL, while the storage deficit for UL and especially R was lower. Including changes in entrapped gas content over the season reduced estimates of changes in water storage at all sites. Because microform type and position were significant predictors of hydrophysical properties, we argue that this suggests that peatland microtopography is self‐reinforcing through ecohydrological feedbacks. Including the variability in these properties in peatland ecohydrological models will be key for predicting the response of peatland ecosystems to disturbance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".