Response of soil nematode community structure and diversity to long‐term land use in the black soil region in China
Bibliographic record
Abstract
Abstract Soil nematodes are sensitive to environmental changes and are used widely as indicators of soil conditions. The community structure and diversity of soil nematodes were studied in different long‐term land use regimes in the black soil area in Northeast China. The land use regimes were maintained for 22 years, and included crop land (CL), grass land (GL) and bare land (BL). Soil samples were taken throughout the growing season, and nematodes were extracted and identified. A total of 39 nematode genera with relative abundance over 0.1 % were identified. Heterodera was the dominant genus in CL; Boleodorus was the dominant genus in GL, and Boleodorus , Eucephalobus and Filenchus were the dominant genera in BL. Land use had a significant effect on abundance of all soil nematode tropic groups and ecological indices. Sampling time had an effect on soil nematode abundance, but only on three of the eight nematode ecological indices MI (maturity index of free‐living nematode), CI (channel index) and EI (enrichment index). SR (species richness index) was highest in GL where plant species diversity was also high. The CI was the highest in BL among three land uses, which means the soil food web dominated, with fungal decomposition channels in BL. Soil nematode community structure and diversity was shown to be an effective and informative tool for analyzing ecological aspects of land use in black soil regions. The data are inconclusive as to whether the effect of land use on soil nematode parameters is direct, or indirect via inducing changes in soil physicochemical properties.
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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 | 0.000 | 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".