The effects of gaps and liming on forest floor decomposition and soil C and N dynamics in a<i>Fagus sylvatica</i>forest
Bibliographic record
Abstract
Despite the importance of gaps in the dynamics and management of many forest types, very little is known about the medium- to long-term soil C and N dynamics associated with this disturbance. This study was designed to test the hypothesis that gap creation and lime application, a routine measure in many European forests to ameliorate soil acidity, lead to accelerated litter decomposition and thus a reduction in the forest floor and soil C and N pools. Four gaps were created in 1989 in a mature European beech (Fagus sylvatica L.) forest on acid soil with a moder humus, and lime (3 t dolomite·ha1) was applied to two of these and surrounding areas. Litter and fine-root decomposition was measured in 19921993 and 19961998 using litterbags. Forest floor (L, F, and H layers) and mineral soil (040 cm) C and N pools were determined in 1989 and 1997. Eight years following silvicultural treatments, there was no change in C and N over the entire forest soil profile including forest floor. Reductions in the F and H layers in limed gaps were compensated for by increases in soil C and N in the surface (010 cm) mineral soil. Decomposition of F litter was significantly accelerated in limed gaps, leading to the development of a mullmoder, whereas gap creation alone had no effect on mass loss of F material in litterbags. Gap size disturbances in this acid beech forest appear to have minimal influences on soil C and N stocks. However, when combined with liming, changes in the humus form and vertical distribution of soil C and N may occur.
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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".