Trade-off between height and branch numbers in Stellera chamaejasme on slopes of different aspects in a degraded alpine grassland
Bibliographic record
Abstract
Aims Trade-off is the basis of life history strategy theory. Elucidation of the trade-off between plant height and branch numbers is important for understanding the phenotypic plasticity of plants under different habitat conditions. Our objective was to examine how Stellara chamaejasme would adapt to changes in slope aspect through trade-off between height and branch numbers. Methods In a degraded alpine grassland on the northern slope of the Qilian Mountains, Gansu Province, China, 80 plots were set up on sites of four different aspects at intervals of 10 m vertically from the foot of an isolated hill moving upward. Handheld GPS was used to record latitude, longitude and altitude of each plot. Community traits were investigated and five S. chamaejasme plants were harvested randomly on each plot for measuring the plant height, brunch numbers, leaf area, and above-ground biomass. ArcGIS was used to construct the digital elevation model(DEM) and to extract data on elevation, aspect, slope, slope of slope, and slope of aspect for the study sites. The 80 plots were categorized into groups of north, east, south, and east aspects. Generalized additive model(GAM) was used to select the most effective terrain factors, and partial correlation analysis method was used to examine the trade-off between plant height and brunch numbers on sites of different aspects. Important findings With a change of the aspect from north to east, south and west, the above-ground biomass and cover of the grassland community displayed a pattern of decline―increase―decline; whereas the average height of the community displayed a pattern of increase―decline. Aspect was the predominant terrain factor affecting spatial variations of the height and branch numbers in S. chamaejasme. When the aspect changed from north and east to west and south, the average height of S. chamaejasme populations declined and the branch numbers increased, resulting in a trade-off in the form of an inversed relationship between the height and branch numbers; whilst the specific leaf area increased first and then decreased. The trade-off between height and branch numbers with changes in slope aspect of the habitat reflected the mechanism of biomass allocation under conditions of multiple competitions for resources in diverse habitats and the regeneration strategy for enhancedadaptation in S. chamaejasme populations.
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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 | 0.000 |
| 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".