Lability of dissolved organic carbon from boreal peatlands: interactions between permafrost thaw, wildfire, and season
Bibliographic record
Abstract
Boreal peatlands are major sources of dissolved organic carbon (DOC) to downstream aquatic ecosystems, where it influences carbon cycling and food web structure. Wildfire and permafrost thaw alter peatland vegetation and hydrology and may affect the quantity and chemical composition of exported DOC. We studied the influence of wildfire and thaw on microbial and photochemical lability of near-surface porewater DOC, assessed through 7 d incubations. We carried out these incubations in spring, summer, and fall but only found differences in spring when DOC biodegradability (% loss during dark incubations) increased with lower DOC aromaticity and C/N ratios. During spring, the most labile DOC was found in recently formed thermokarst bogs along collapsing peat plateau edges (25% loss), which was greater than in mature sections of thermokarst bogs (3%), and peat plateaus with intact permafrost (9%). Increased DOC lability following thaw was likely linked to high DOC production and turnover associated with productive hydrophilic Sphagnum mosses and sedges, rather than thawed permafrost peat. A wildfire (3 yr prior) reduced DOC biodegradability in both peat plateaus (4%) and rapidly collapsing peat plateau edges (14%). Biodegradability of DOC in summer and fall was low across all sites; 2% and 4%, respectively. Photodegradation was shown to potentially contribute significantly to downstream DOC degradation but did not vary across peatland sites. We show that disturbances such as permafrost thaw and wildfire have the potential to affect downstream carbon cycling, particularly as the largest influences were found in spring when peatlands are well connected to downstream aquatic ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 |
| 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 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".