Hydrogeologic setting overrides any influence of wildfire on pore water dissolved organic carbon concentration and quality at a boreal fen
Bibliographic record
Abstract
Abstract Western Boreal Canada could experience drier hydrometeorological conditions under future climatic changes, and the drying of nonpermafrost peatlands can lead to higher frequency and extent of wildfires. Despite increasing pressures, our understanding of the impact of fire on dissolved organic carbon (DOC) concentration and quality across boreal peatlands is not consistent. This study capitalizes on the rare opportunity of having 3 years of prefire and 3 years of postfire DOC data at a treed, moderate‐rich fen in the Western Boreal Plain, northern Alberta, to investigate wildfire effects on peatland DOC dynamics. We investigated whether a wildfire facilitated any changes in the pore water DOC concentration and quality. There was very little impact of the fire directly, with no significant changes in DOC concentrations postfire. We highlight that DOC patterns are more likely to be controlled by local hydrogeological factors than any effect of fire. Fall hydrological conditions and subsequent winter storage processes impose a strong control on DOC concentrations the following year. We suggest that the presence or absence of concrete ground frost in the fen (determined by fall water table position) influences overwinter storage changes, controlling the effect that DOC‐poor snowmelt may have on pore water concentrations. However, an increase in SUVA254 was found 2 years postfire, indicating an increase in aromaticity. These results highlight the need for careful consideration of the local hydrogeologic setting and hydrological regime when predicting and analysing trends in DOC concentrations and quality.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".