DOM composition and transformation in boreal forest soils: The effects of temperature and organic‐horizon decomposition state
Bibliographic record
Abstract
Abstract The boreal region stores large amounts of organic carbon (C) in organic‐soil horizons, which are vulnerable to destabilization via warming and disturbance. Decomposition of soil organic matter (SOM) contributes to the production and turnover of dissolved organic matter (DOM). While temperature is a primary control on rates of SOM and DOM cycling, little is known about temperature effects on DOM composition in soil leachate. Here we conducted a 30 day incubation to examine the effects of temperature (20 versus 5°C) and SOM decomposition state (moss versus fibric versus amorphous horizons) on DOM composition in organic soils of interior Alaska. We characterized DOM using bulk dissolved organic C (DOC) concentration, chemical fractionation, optical properties, and ultrahigh‐resolution mass spectrometry. We observed an increase in DOC concentration and DOM aromaticity in the 20°C treatment compared to the 5°C treatment. Leachate from fibric horizons had higher DOC concentration than shallow moss or deep amorphous horizons. We also observed chemical shifts in DOM leachate over time, including increases in hydrophobic organic acids, polyphenols, and condensed aromatics and decreases in low‐molecular weight hydrophilic compounds and aliphatics. We compared ultrahigh‐resolution mass spectrometry and optical data and observed strong correlations between polyphenols, condensed aromatics, SUVA254, and humic‐like fluorescence intensities. These findings suggest that biolabile DOM was preferentially mineralized, and the magnitude of this transformation was determined by kinetics (i.e., temperature) and substrate quality (i.e., soil horizon). With future warming, our findings indicate that organic soils may release higher concentrations of aromatic DOM to aquatic ecosystems.
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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".