Decomposer invasion rate, decomposer growth rate, and substrate chemical quality: how they influence soil organic matter turnover
Bibliographic record
Abstract
The physical structure of litter can be introduced into decomposition models in several ways. We have used the continuous-quality theory to analyse three models: (i) initial quality of litter or growth rate of decomposers depends on the physical structure of litter, (ii) decomposer colonization rate of litter depends on litter shape and size, and (iii) a constant decomposition rate, i.e., no effect of litter shape and size. Our analysis shows that it is important to separate the physical factors affecting access to carbon (C), i.e., decomposer colonization rate, from the chemical characteristics of litter in decomposition models. Soil C stores predicted with models based on the colonization rate of decomposers are much less sensitive to the shape and size of coarse woody litter than predictions based on the two other approaches. The effect of temperature on steady-state soil C storage is greater for litter that is colonized rapidly than for litter that is colonized slowly. The decomposition of litter types like needles, fine roots, and field-layer vegetation is therefore more sensitive to temperature changes than the decomposition of stems and coarse roots, and this difference is more pronounced at high temperatures than at low temperatures.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".