Controlling Soil Factor in Plant Growth and Salt Tolerance of Leguminous Plant Alhagi sparsifolia Shap. in Saline Deserts, Northwest China
Bibliographic record
Abstract
The understanding of relationships between the plants and environmental variables is important for ecological restoration. The objective of this research was to investigate the controlling soil factor in plant growth and salt tolerance of leguminous plant Alhagi sparsifolia Shap. ( A. sparsifolia ) in a saline desert ecosystem of western China. Results showed that coverage of A. sparsifolia was positively linked to soil total K. A. sparsifolia accumulated the toxic Na + in either roots or stems and thus reduced their allocation in the leaves to adapt the salt stress. The most important factor that determined Na + uptake of A. sparsifolia was soil total K content, which suggests that total K can alleviate toxic Na + accumulation in A. sparsifolia . In addition, there was a significant negative correlation among toxic Cl − concentration in A. sparsifolia , soil total K and pH. Overall, soil total K accounted for 18.2% of plant growth and salt tolerance of A. sparsifolia , followed by soil pH 13.1%, and soil total P 11.6%. In order to restore A. sparsifolia in the degraded desert ecosystems on salinized soil, first we need to consider the effects of soil total K, and then synergistically consider the soil pH and total P.
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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 | 0.000 | 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) | 0.000 | 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".