Tree rings used to assess time since death of deadwood of different decay classes in beech and silver fir forests in the central Apennines (Molise, Italy)
Bibliographic record
Abstract
We investigated the relationship between time since death and morphological characteristics of Abies alba Mill. (European silver fir) and Fagus sylvatica L. (European beech) stumps in two forest stands in the central Apennines. At each site, 15 or 16 living trees were selected, and increment cores were collected to build master ring-width chronologies. For both sites, cross sections were collected from stumps. Samples were assigned to visually discernible decay classes, and their death date dendrochronologically determined. Using cross-dating techniques, stumps cross-dated significantly with standard chronologies, and it was possible to assign a year of death to 77% and 69% of sampled A. alba and F. sylvatica stumps, respectively. Analysis of the time since death of the stumps suggests that the two species have similar decay rates, although A. alba was faster in passing from class 2 to class 3. However, this study revealed a continuum through decay classes and showed a high variability in the transition rate from one class to another. Overall, information obtained using dendrochronological techniques was valuable for assessing deadwood decomposition rates. The variability found in stump decomposition rates indicates that existing decay classification schemes, although providing information on decomposition timing, are hardly applicable to these forest stands and that the relationship between qualitatively assessed decay classes and time since death of trees appears to be rather weak.
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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 | 0.001 |
| 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 | 0.000 | 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".