Size-asymmetric and spatially structured competition shapes Populus euphratica stands in the lower Tarim river riparian zone
Bibliographic record
Abstract
Hydrological alteration and groundwater decline have reshaped the structure of Populus euphratica riparian forests along the lower Tarim River, underscoring the need for structural indicators that diagnose neighborhood crowding and guide restoration. We quantified intraspecific competition using Hegyi’s competition index (CI) across six 50 × 50 m plots arrayed along a river-distance (hydrological-edaphic gradient), measuring DBH, height, crown area, and spatial position for 229 target trees. We treat river distance as a hydrological-edaphic gradient proxy rather than a single causal factor and evaluate CI jointly with tree size and local stem density to avoid over-attribution to distance alone. We tested three hypotheses: (i) competition intensity decreases with tree size (DBH, height, crown area); (ii) competition peaks at intermediate distance from the river; and (iii) competition intensity increases with local stem density. Because CI integrates neighbor size and spacing, it serves as a management-relevant structural indicator of local crowding and stand condition. CI declined strongly with DBH and height (size-asymmetric competition), showed a bimodal pattern across crown-area classes (peaks at 0–10 m 2 and 30–40 m 2 ), and reached a spatial maximum at ∼ 300 m from the river where stem density was highest. Class-level models corroborated a negative DBH effect on CI (p < 0.05) and weak quadratic terms for crown area; CI was positively associated with local stem density. These results identify structural thresholds (≤20 cm DBH; 0–2 m height; <10 m 2 crown area) and a mid-gradient crowding peak (∼300 m) that together diagnose where regulation should be prioritized. Management implications include selective release thinning of dense sapling clusters and conditional, small-pulse ecological water supplementation where site diagnostics indicate hydrologic limitation, coupled with long-term monitoring of density, size trajectories, and mortality.
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How this classification was reachedexpand
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 | 0.001 |
| 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 teacher head, 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".