Tree-line dynamics in relation to climate variability in the Shennongjia Mountains, central China
Bibliographic record
Abstract
Subalpine tree lines are particularly sensitive to climate variability. In this study, tree-ring chronologies and age structure of the subalpine fir Abies fargesii Franch. are developed to examine subalpine tree-line dynamics in relation to climate variability on the northern and southern aspects of the Shennongjia Mountains in central China. Response function analysis shows that radial growth is significantly positively correlated with temperatures during the previous November and in February and March of the current year on the northern aspect and with temperatures during the previous October and in March, April, and June of the current year on the southern aspect. Recruitment of A. fargesii is positively influenced by temperature in March and April on the northern aspect and in February, March, and May on the southern aspect. Precipitation shows no significant correlation with radial growth or recruitment of A. fargesii on either aspect. Thus, spring temperatures are the major factor limiting both radial growth and seedling establishment of this subalpine fir species. Radial growth and recruitment of A. fargesii show similar responses to climate variability and provide critical information for assessing the impacts of climate warming on tree-line dynamics, such as an increase in tree density and an upward shift of the altitudinal tree line in this mountainous region of central China.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".