Exploring the optimal grazing intensity in desert steppe based on soil nematode community and function
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Grazing is a key regulator of the biodiversity of the desert steppe in Inner Mongolia and has important ecological significance for the sustainable development of underground ecosystems. In a 14‐year grazing intensity experiment, we systematically explored the changes in soil nematode communities in desert steppe soils and comprehensively evaluated the optimal grazing intensity for the sustainability of the desert steppe underground ecosystem. Using high‐throughput sequencing, we analyzed the soil nematode communities and their relationships with environmental factors. The 14‐year grazing experiment revealed a significant impact on the diversity and composition of the soil nematode community in the surface layer (0–10 cm) and on the soil nematode community in the whole soil layer (0–20 cm). Based on LEfSe multilevel discriminant analysis, we found that the relative abundances of Acrobeles , Cephalobus , Filenchus , Aphelenchus , Longidorella , Amplimerlinius , Aporcelaimellus , Acrobeloides , Dorylaimellus , Hemicycliophora , Thonus , Alaimus , and Oxydirus changed significantly under different grazing treatments. Considering the number and function of soil nematode communities, long‐term light grazing was found to significantly promote an increase in soil nematode diversity and helped maintain soil nematode community stability. We determined that the most suitable grazing intensity for the sustainability of the soil underground ecosystem of the desert steppe in Inner Mongolia is light grazing (0.91 sheep hm ‐2 0.5 yr ‐1 ). We have, thus, provided a tool for determining and evaluating optimal grazing intensities for sustainable soil underground ecosystems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it