Stoichiometric homeostasis of Morus alba in the dry-hot valley
Bibliographic record
Abstract
Introduction Stoichiometric homeostasis is an important strategy used by plants to function optimally in changing environments. Methods In order to investigate whether plants under stricter resource restrictions exhibit stronger homeostasis, this study took M. alba inhabiting in a dry-hot valley as the research subject. Results The stoichiometry of M. alba leaves, their variations in response to altitude and slope, and their correlations with soil were analyzed. The results showed that soil nutrient levels were higher on the shady slope compared to the sunny slope, and responded differently to altitude on the two slopes. On the sunny slope, soil carbon (C) content increased significantly with altitude, whereas on the shady slope, soil phosphorus (P) content decreased with increasing altitude. The C: N and C: P ratios of the soil were lower than the average in China. The C: N and C: P ratios of M. alba leaves were lower than those of global and Chinese forest ecosystems. The N: P ratio of M. alba leaves was < 14. However, no significant correlation was observed between M. alba leaves and soil C, N, P, or stoichiometric characteristics. The changes in C, N, and P and their ratios in M. alba leaves did not correspond with those in the soil. M. alba exhibited "strict homeostasis" on both sunny and shady slopes. Discussion The results suggest that M. alba's growth is limited by nutrients availability, particularly nitrogen. The strict stoichiometric homeostasis is an adaptation strategy for M. alba in dry-hot valleys to alleviate nutrient limitations, which leads to a decoupling of ecological stoichiometry between M. alba leaves and soil.
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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".