Chemical transformations in downed logs and snags of mixed boreal species during decomposition
Bibliographic record
Abstract
Snags and downed logs are substantial components of the detrital carbon pool in boreal forests. Effects of their decomposition on chemical and physical characteristics of the forest floor remain relatively unknown. The main objective of this study was to characterize chemical transformations of decaying logs and snags of common tree species in the boreal mixedwood forest. Logs and snags from a wide range of decay classes were sampled and analyzed by solid-state 13C nuclear magnetic resonance spectroscopy and by near-infrared spectroscopy. Little or moderate chemical changes appeared in fresh and moderately decayed snags and logs, but in well-decayed logs, substantial degradation of carbohydrates and increases in lignin concentrations occurred. Deciduous species had initially more carbohydrates than coniferous species, but decomposition narrowed their differences, and in well-decayed logs, species differed mainly in terms of their lignin concentrations. Well-decayed deciduous logs reached very low wood densities, and their integration into the forest floor and long-term preservation remains questionable. In contrast, chemical composition of well-decayed coniferous logs resembles that of lignic forest floor (i.e., forest floor originating from deadwood decomposition), with preserved lignins, carbohydrates, and alkyl carbon compounds. Decomposed coniferous wood thus contributes to chemical heterogeneity of the forest floor, possibly promoting diversity of decomposers as well as carbon retention in soils.
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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 | 0.001 | 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".