Long-Term Nitrogen Addition Alters the Composition of Soil-Derived Dissolved Organic Matter
Bibliographic record
Abstract
Forest soil dissolved organic matter (DOM) is a major source of terrigenous dissolved organic carbon (DOC) that is an important component of biogeochemical cycles. While many studies have shown that DOM dynamics are regulated strongly by nitrogen availability, how continued or increasing deposition of reactive nitrogen to forests alters the molecular composition of soil DOM remains unexplored. We studied the storage and molecular-level composition of soil-derived DOM after 22 years of nitrogen addition in a temperate deciduous forest. Soil DOC quantity changes were small (+19.0 g/m2; ∼10% increase) but the molecular composition changed markedly. Indices based on optical spectroscopy suggested that DOM molecular size and aromaticity were elevated with nitrogen addition. Nuclear magnetic resonance analyses showed that DOM contained more carbohydrates and aromatics but less aliphatic compounds with nitrogen addition. Ultrahigh-resolution mass spectrometric analysis further supports the finding that solid-phase isolated DOM from nitrogen-added soils was larger in molecular size and aromaticity. Condensed aromatic dissolved black carbon, particularly those compounds with high molecular size/carbon number and those stored in deep soils, showed the greatest percent increase with nitrogen addition. These results countered our hypothesis that soluble carbohydrates would be selectively removed from the DOC pool compared to polyphenols and condensed aromatic components under nitrogen enrichment. These changes in DOM molecular composition may also impact microbial communities and downstream metabolism of DOC.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".