Freeze-thaw cycles alter soil hydro-physical properties and dissolved organic carbon release from peat
Bibliographic record
Abstract
The ongoing climate warming is likely to increase the frequency of freeze-thaw cycles (FTCs) in cold-temperate peatland regions. Despite the importance of soil hydro-physical properties in water and carbon cycling in peatlands, the impacts of FTCs on peat properties as well as carbon sequestration and release remain poorly understood. In this study, we collected undisturbed topsoil samples from two drained lowland fen peatlands to investigate the impact of FTCs on hydro-physical properties as well as dissolved organic carbon (DOC) fluxes from peat. The soil samples were subject to five freeze-thaw treatments, including a zero, one, three, five, ten cycles (FTC0, FTC1, FTC3, FTC5, and FTC10, respectively). Each FTC was composed of 24 h of freezing (−5°C) and 24 h of thawing (5°C) and the soil moisture content during the freeze-thaw experiment was adjusted to field capacity. The results showed that the FTCs substantially altered the saturated hydraulic conductivity (Ks) of peat. For peat samples with low initial Ks values (e.g., < 0.2 × 10−5 m s−1), Ks increased after FTCs. In contrast, the Ks of peat decreased after freeze-thaw, if the initial Ks was comparably high (e.g., > 0.8 × 10−5 m s−1). Overall, the average Ks values of peatlands decreased after FTCs. The reduction in Ks values can be explained by the changes in macroporosity. The DOC experiment results revealed that the FTCs could increase DOC concentrations in leachate, but the DOC fluxes decreased mainly because of a reduction in water flow rate as well as Ks. In conclusion, soil hydraulic properties of peat (e.g., Ks) are affected by freezing and thawing. The dynamics of soil hydraulic properties need to be explicitly addressed in the quantification and modelling of the water flux and DOC release from peatlands.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".