Initial turnover rates of two standard wood substrates following land-use change in subalpine ecosystems in the Swiss Alps
Bibliographic record
Abstract
Forest cover has increased in mountainous areas of Europe over the past decades because of the abandonment of agricultural areas (land-use change). For this reason, understanding how land-use change affects carbon (C) source–sink strength is of great importance. However, most studies have assessed mountainous systems C stocks, and less is known about C turnover rates, especially of “fresh” organic material (OM). We studied the decomposition of wood stakes of trembling aspen (Populus tremuloides Michx.) and loblolly pine (Pinus taeda L.) placed on the litter layer and in the mineral soil of five ecosystem types (pastures and forests) — representing the successional development after land abandonment in the eastern Swiss Alps — for 6 years. Wood stake decomposition rates were generally highest in pastures and lowest in early successional forests. Aspen stakes decomposed more rapidly than pine stakes, especially in the mineral soil. Soil temperature (and to a smaller extent soil phosphorus (P) concentration) best explained the differences in decomposition among the ecosystem types. Initial wood decay is temperature-sensitive, and therefore would likely increase under future climate change scenarios.
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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 | 0.001 |
| 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 | 0.001 | 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".