Tree stratum alteration decreases C use efficiency and the stability of litter decomposition in a sacred fir ( Abies religiosa ) forest
Bibliographic record
Abstract
Background: There is limited information to predict the direction in which canopy modification affects the microbial carbon use efficiency (CUE) and, consequently, the magnitude and stability of litter decomposition in monodominant sacred fir ( Abies religiosa ) forests. Questions: What is the effect of tree stratum alteration on CUE and stability of litter decomposition in an A. religiosa forest? Study sites and dates: Two conditions inside a sacred fir forest were selected: A) a naturally monodominant homogeneous condition, and B) a heterogeneous condition with a non-monospecific tree stratum derived from local disturbances (wildfire and reforestation) occurred on a single occasion 18 years ago. Methods: In each condition (homogeneous and heterogeneous), the Importance Value Index (IVI) was calculated in the tree stratum, while chemical composition, microbial carbon (C) concentration, enzyme activities and C mineralization were measured in litter samples. The specific enzymatic activity and the metabolic quotient were calculated as CUE indicators, and the coefficient of variation as a proxy for litter decomposition stability. Results: A change in tree species composition and an increase in tree species richness in the heterogeneous condition was found, which decreased litter phosphorous (P) concentration. This promoted a high microbial activity and low CUE, favoring C mineralization. Furthermore, low stability during litter decomposition was observed as tree species richness increased. Conclusions: Tree stratum heterogeneity, as a consequence of past disturbances, decreases CUE and the stability of litter decomposition in an A. religiosa forest.
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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".