Nutrient fluxes via leaching from coarse woody debris in a Fagus sylvatica forest in the Solling Mountains, Germany
Bibliographic record
Abstract
To evaluate the importance of nutrient fluxes via leaching from coarse woody debris (CWD) in an area with high atmospheric nitrogen (N) inputs, throughfall and CWD leachate from logs at different stages of decomposition were investigated over a period of 14 and 27 months, respectively, in a 160-year-old European beech ( Fagus sylvatica L.) forest in northwestern Germany. Water samples, collected from 30 zero-tension lysimeters installed in pairs along 15 logs and from 27 neighboring raingauges, were chemically analyzed in the laboratory. Generally, as CWD decay advanced, the ratio of leachate to throughfall decreased, and the amount of dissolved nutrients in the leachate increased. With the exception of ammonium (NH4+) and dissolved inorganic carbon, the element concentrations in the CWD leachate were significantly higher than those in the throughfall. The concentrations of NH4+and nitrate (NO3–) in the CWD leachate, which were very high compared with values from North American studies, were caused by the continuously high atmospheric N inputs, and the resulting N saturation in the forest ecosystem investigated. The low concentrations of the cations calcium and magnesium indicate that at this site nutrients limiting plant and fungal growth are retained and accumulated in the CWD.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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".