Chemical changes in organic matter after fungal colonization in a nitrogen fertilized and unfertilized Norway spruce forest
Bibliographic record
Abstract
BACKGROUND AND AIMS: Decomposition and transformation of organic matter (OM) in forest soils are conducted by the concomitant action of saprotrophic and mycorrhizal fungi. Here, we examine chemical changes in OM after fungal colonization in nitrogen fertilized and unfertilized soils from a Norway spruce forest. METHODS: Sand-filled bags amended with composted maize leaves were placed in the forest soil and harvested after 17 months. Infrared and near edge X-ray absorption fine structure spectroscopies were used to study the chemical changes in the OM. Fungal community composition of the bags was also evaluated. RESULTS: The proportion of ectomycorrhizal fungi declined in the fertilized plots, but the overall fungal community composition was similar between N treatments. Decomposition of the OM was, independently of the N level or soil horizon, accompanied by an increase of C/N ratio of the mesh-bag content. Moreover, the proportions of carboxylic compounds in the incubated OM increased in the mineral horizon, while heterocyclic-N compounds decreased, especially in unfertilized plots with higher N demand from the trees. CONCLUSIONS: Our results indicate that more oxidized organic C and less heterocyclic-N proportions in the OM remain after fungal colonization in the mineral layers, and suggest that ectomycorrhizal fungi transfer less heterocyclic-N from the mesh bags to the host trees under high N levels.
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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 | 0.000 | 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".