Soil weathering dynamics and erosion in a dry oceanic area of the southern hemisphere (Otago, New Zealand)
Bibliographic record
Abstract
Abstract Landscape evolution is driven by tectonics, climate and surface denudation. In New Zealand, tectonics and steep climatic gradients cause a dynamic landscape with intense chemical weathering, rapid soil formation, and high soil losses. In this study, soil, and elemental redistribution along two adjacent hillslopes in East Otago, New Zealand, having different landscape settings (ridge versus valley) are compared to identify soil weathering and erosion dynamics. Fallout radionuclides ( 239+240 Pu) show that over the last ~ 60 years, average soil erosion rates in the valley (~ 260 [t km −2 year −1 ]) are low compared to the ridge (~ 990 [t km −2 year −1 ]). The ridge yields up to 26% lower soil weathering intensity than the topographical-protected valley. The lowest soil weathering intensity is found at both hilltop positions, where tors (residual rocks) are present and partially disintegrate. The soil weathering intensity increases with distance from tors, suggesting that tors rejuvenate the chemical weathering signature at the hilltop positions with fresh material. The inversed and decreasing weathering degree with all soil depth indicates that the fresh mineral contribution must be higher at the soil surface than at the bedrock weathering front. Higher erosion rates at the exposed ridge may be partially attributed to wind, consistent with rock abrasion of tors, and low local river sediment yields (56 [t km −2 year −1 ]). Thus, the East Otago spatial patterns of soil chemistry and erosion are governed by tor degradation and topographic exposure.
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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".