Gas exchange and resource utilization in two alpine oaks at different altitudes in the Hengduan Mountains
Bibliographic record
Abstract
The evergreen sclerophyllous broadleaf forests composed of alpine oaks in the Hengduan Mountains of southwest China are mainly distributed at altitudes of 1700–4800 m. Gas exchange and related leaf traits of Quercus guyavifolia H. Lév. and Quercus pannosa Hand.-Mazz. were measured at eight sites along an altitudinal gradient to understand their physiological adaptabilities. Both Q. guyavifolia and Q. pannosa showed a significant midday depression in the photosynthesis rate (PN) due to a high vapor pressure deficit and high temperature around noon. The optimum temperature for photosynthesis for the two oak species ranged from 17 to 23 °C depending on altitude. When the temperature exceeded 25 °C, PN decreased sharply. However, PN was not depressed by high irradiance. As altitude increased, the leaf dry mass per unit area of the two oaks increased but the chlorophyll content decreased, while the maximum values of daily mean photosynthesis rate (Pd), maximum photosynthesis rate (Pmax), Pd/Pmax, water-use efficiency, and photosynthetic nitrogen use efficiency occurred at altitudes of 3240–3610 m. Although the photosynthetic capacities of the two oaks were higher in August than in May, altitudinal trends did not change with season. The altitudinal range from 3240 to 3610 m would be optimal for the growth and development of these two alpine oaks in the Hengduan Mountains.
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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 | 0.001 | 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".