Grazing Effects on Compressibility of Kastanozems in Inner Mongolian Steppe Ecosystem
Bibliographic record
Abstract
In Inner Mongolia, animal trampling is one of the main factors causing soil degradation manifested by altered mechanical strength or changes in water and gas fluxes. Soil samples were collected at two depths (4–8 and 18–22 cm) on the Stipa grandis steppe ecosystem in Inner Mongolia from two treatments characterized by different grazing intensities: ungrazed since 1979 (UG) and continuously grazed (CG). The following mechanical soil properties were determined under static and repeated loading conditions: precompression stress, P c ; coefficient of cyclic compressibility, c n , and compression index, C c Air conductivity measurements were used to quantify the changes in soil functions due to application of repeated loading. The CG site showed significantly higher precompression stress values (111 kPa) than the UG site (64 kPa) at the first soil depth. The highest c n values were found in the topsoil of the UG site, while the CG site had significantly lower c n values. Repeated loading caused higher soil deformation compared to the static loading test. It was also found that the strain of soil samples from the UG site was higher than the CG site. We found a good fit between c n and precompression stress. The C c values of the cyclically loaded samples were significantly lower at the CG site than the statically loaded ones. The air conductivity of the UG site remained constant for a wider stress range of repeatedly applied stress compared with the CG site, which reflects higher stability of the soil pore network at the UG site.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".