Soil erodibility in European mountain beech forests
Bibliographic record
Abstract
Forests in Europe are currently not endangered by soil erosion. However, this can change with climate change or with intensified forest management practices. Using a newly established network of plots in beech forests across Europe, the aims of this study were to (i) distinguish soil properties and erodibility indices in relation to bedrock, (ii) determine geochemical properties and organic carbon (Corg) influencing erodibility, and (iii) assess the effect of soil depth on erodibility indices. Seventy-six soil samples from 20 beech forests were collected in 11 countries to quantify soil properties influencing erodibility indices: clay ratio, modified clay ratio, sodium adsorption ratio, and oxides ratio. The results indicate that the dominant soil properties, determined by bedrock, that correlate with forest soil erodibility indices are Corg, pH, electrical conductivity, calcium and sodium ions concentrations, total water-soluble cations, and the percentage of sand. According to the tested indices, soil susceptibility to erosion follows the order granite > andesite > sandstone > quartzite > limestone. Deeper soil horizons on granite are more susceptible to erosion than surface horizons are, but this is not the case for soils on limestones. In conclusion, forest management should consider the predisposition of different soil types to erosion.
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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 | 0.001 |
| 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) | 0.000 | 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".