The salt secretion of leaves promotes the competitiveness of Reaumuria soongarica in a desert grassland
Bibliographic record
Abstract
BACKGROUND: For better understanding the mechanism of Reaumuria soongarica community formation in a salt stressed grassland ecosystem, we designed a field experiment to test how leaves salt secretion changes the competitive relationship between species in this plant communities. RESULTS: Among the three species (R. soongarica, Stipa glareosa and Allium polyrhizum) of the salt stressed grassland ecosystem, the conductivity of R. soongarica rhizosphere soil was the highest in five soil layers (0-55 cm depth). The high soil conductivity can increase the daily salt secretion rate of plant leaves of R. soongarica. In addition, we found the canopy size of R. soongarica was positively related to the distance from S. glareosa or A. polyrhizum. The salt-tolerance of R. soongarica was significantly higher than the other two herbs (S. glareosa and A. polyrhizum). Moreover, there was a threshold (600 µS/cm) for interspecific competition of plants mediated by soil conductivity. When the soil conductivity was lower than 600 µS/cm, the relative biomass of R. soongarica increased with the soil conductivity increase. CONCLUSIONS: The efficient salt secretion ability of leaves increases soil conductivity under the canopy. This leads the formation of a "saline island" of R. soongarica. Meanwhile R. soongarica have stronger salt tolerance than S. glareosa and A. polyrhizum. These promote the competitiveness of R. soongarica and inhibit interspecies competition advantage of the other two herbs (S. glareosa and A. polyrhizum) in the plant community. It is beneficial for R. soongarica to establish dominant communities in saline regions of desert grassland.
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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".