Plant Evolution History Overwhelms Current Environment Gradients in Affecting Leaf Chlorophyll Across the Tibetan Plateau
Bibliographic record
Abstract
Aims Leaf chlorophyll (Chl) is a fundamental component and good proxy for plant photosynthesis. However, we know little about the large-scale patterns of leaf Chl and the relative roles of current environment changes vs. plant evolution in driving leaf Chl variations. Locations The east to west grassland transect of the Tibetan Plateau. Methods We performed a grassland transect over 1,600 km across the Tibetan Plateau, measuring leaf Chl among 677 site-species. Results Leaf Chl showed a significantly spatial pattern across the grasslands in the Tibetan Plateau, decreasing with latitude but increasing with longitude. Along with environmental gradient, leaf Chl decreased with photosynthetically active radiation (PAR), but increased with water availability and soil nitrogen availability. Furthermore, leaf Chl also showed significant differences among functional groups (C4 > C3 species; legumes < non-legume species), but no difference between annual and perennial species. However, we surprisingly found that plant evolution played a dominant role in shaping leaf Chl variations when comparing the sum and individual effects of all the environmental factors above. Moreover, we revealed that leaf Chl non-linearly decreased with plant evolutionary divergence time. This well-matches the non-linearly increasing trend in PAR or decreasing trend in temperature during the geological time-scale uplift of the Tibetan Plateau. Main Conclusion This study highlights the dominant role of plant evolution in determining leaf Chl variations across the Tibetan Plateau. Given the fundamental role of Chl for photosynthesis, these results provide new insights into reconsidering photosynthesis capacity in alpine plants and the carbon cycle in an evolutionary view.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".