The woody plant <i>Haloxylon ammodendron</i> (C.A. Mey.) provides new insights into the self-thinning relationship and size inequality with wind erosion stress
Bibliographic record
Abstract
The self-thinning process and size inequality of plants change with age and wind erosion stress conditions. In this study, we used Haloxylon ammodendron (C.A. Mey.) shrubs in their juvenile stage (1–6 years) as the study subjects. Their density, height, and survival were investigated. The relationship between the mean and variation in the densities was calculated using Taylor’s power law, and the change laws of the density clustering state were analyzed. Additionally, changes in size inequality and the self-thinning process were examined. The results indicated that under the same wind erosion stress, the self-thinning slope was positive ( P < 0.05); the shrub density aggregation of H. ammodendron became denser with increasing wind erosion stress. The size inequality first increased and then decreased as the developing stage progressed. Under the same stress, the competition index increased with increasing age and decreased with increasing stress. We demonstrated that under a harsher microenvironment for plant growth, plants’ clustering and growth increased facilitation, resulting in a shift in the net effect of the positive and negative interactions between individuals. Furthermore, the results revealed that as age increased, the size inequality was left-skewed.
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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) | 0.001 | 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".