Hydrological conditions control dissolved organic matter dynamics along a peatland headwater boreal stream
Bibliographic record
Abstract
Hydrological conditions (i.e., high-flow versus low-flow) in peatland drainage streams influence both the quantity of dissolved organic carbon (DOC) exports and dissolved organic matter (DOM) composition. Yet, our knowledge on DOM fate after exports from the peatland remains limited while this highly reactive component sustains emissions and exports of carbon dioxide (CO2) from streams through degradation processes. The present study demonstrates the relationships between DOM composition evolution and catchment hydrological conditions along a 3 km long headwater stream running through a boreal peatland, from its source to the outlet. Our results show that hydrological conditions significantly influenced DOM composition evolution along the stream. DOM exported during high-flow conditions presented a composition similar to peat porewater in terms of DOC:DON ratio and aromaticity, but a lower average molecular weight, indicating preferential exports of low molecular weight DOM recently produced in the acrotelm. The DOM composition changed little along the stream during high-flow as it was rapidly flushed downstream. During low-flow conditions, DOM composition evolved along the stream in contrast to high-flow with a strong increase in DOM aromaticity and molecular weight along the stream. These changes were significantly correlated to the water residence time in the stream and to the estimated proportion of mineralized DOC to total DOC flux exported at the stream outlet. These results highlight the importance of hydrological conditions on DOM dynamics as DOM was locally mineralized during low-flow conditions, when DOC exports were low, while mineralization processes happened downstream under high-flow conditions which favored important DOC exports.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".