Contrasting soil dynamics in the Serra da Estrela mountain plateau –  Portugal
Bibliographic record
Abstract
Limited data are available on how soil erosion rates compare between surfaces of different ages because short-term processes often overprint the longer-term erosion signal. This study investigated the soil dynamics among a formerly glaciated ('young', maximum glacial extent at 22–30 ka BP) and a non-glaciated ('old') area in the Serra da Estrela (Portugal). To disentangle soil distribution rates over different timeframes, isotopes for long-term (10Be), mid-term (δ13C) and short-term (239+240Pu) periods were applied together with principles of the percolation theory. Soils at the formerly glaciated area have a lower degree of weathering and lower carbon content compared to soils of the ‘older’, non-glaciated area. The distribution of selected isotopes along the soil profiles revealed temporal differences in soil mixing process. The formerly glaciated surface resulted in higher long-term average erosion rates compared to the non-glaciated area. Yet, soil redistribution rates over the last few decades are up to one order of magnitude higher than the millennia rates. Human impact (bush fires, grazing) is considered the probable cause for the currently strong soil degradation.
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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 | 0.001 |
| 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) | 0.001 | 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".