Effects of Warming on Chlorophyll Degradation and Carbohydrate Accumulation of Alpine Herbaceous Species during Plant Senescence on the Tibetan Plateau
Bibliographic record
Abstract
Plant senescence is a critical life history process accompanied by chlorophyll degradation and has large implications for nutrient resorption and carbohydrate storage. Although photoperiod governs much of seasonal leaf senescence in many plant species, temperature has also been shown to modulate this process. Therefore, we hypothesized that climate warming would significantly impact the length of the plant growing season and ultimate productivity. To test this assumption, we measured the effects of simulated autumn climate warming paradigms on four native herbaceous species that represent distinct life forms of alpine meadow plants on the Tibetan Plateau. Conditions were simulated in open-top chambers (OTCs) and the effects on the degradation of chlorophyll, nitrogen (N) concentration in leaves and culms, total non-structural carbohydrate (TNC) in roots, growth and phenology were assessed during one year following treatment. The results showed that climate warming in autumn changed the senescence process only for perennials by slowing chlorophyll degradation at the beginning of senescence and accelerating it in the following phases. Warming also increased root TNC storage as a result of higher N concentrations retained in leaves; however, this effect was species dependent and did not alter the growing and flowering phenology in the following seasons. Our results indicated that autumn warming increases carbohydrate accumulation, not only by enhancing activities of photosynthetic enzymes (a mechanism proposed in previous studies), but also by affecting chlorophyll degradation and preferential allocation of resources to different plant compartments. The different responses to warming can be explained by inherently different growth and phenology patterns observed among the studied species. The results implied that warming leads to changes in the competitive balance among life forms, an effect that can subsequently shift vegetation distribution and species composition in communities.
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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".