Effect of stand age on fine-root biomass and biomass distribution in three European forest chronosequences
Bibliographic record
Abstract
Fine-root (<2 mm) biomass and biomass distribution were determined in different age-classes of three European forest chronosequences dominated by Fagus sylvatica L., Picea abies (L.) Karst., and Quercus cerris L., respectively. Root samples were taken with the auger method. There was a clear effect of stand age on standing fine-root biomass, with the highest fine-root biomass in adult but not mature stands. The vertical fine-root biomass distribution showed, at all sites, high densities of roots in the top soil layers and with depth a gradual decrease of fine-root biomass density. The difference in total fine-root biomass between the different age-classes appeared to be due to differences in the top soil layers. Fine-root biomass in the lower soil layers was less variable along the life cycle of the forests. Only in very young stands, specific root length of fine roots was higher than in the other age-classes. The present data together with other published values suggest that fine-root biomass in tree stands develops in three phases: rapid increase after a clear-cut harvest up to a maximum of fine-root biomass; a decrease during maturation of the stand; and a steady-state in mature stands.
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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) | 0.001 | 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".