Tree-ring climate response of chir-pine (Pinus roxburghii Sarg.) in the sub-tropical forest, western Nepal
Bibliographic record
Abstract
ABSTRACT A dendrochronological study was carried out to investigate the relationship between the growth of chir pine (Pinus roxburghii) and climatic variables in the subtropical forest of western Nepal.Using tree ring analysis and meteorological data gathered from a nearby meteorological station, a 78-year (1944 to 2021) long chronology has been created. Temperature and precipitation were found to have a substantial impact on P. roxburghii radial growth. Although there were positive correlations between precipitation and tree growth in January, December, and February to April, these relationships were not statistically significant. According to the correlation analyses, there was a negative relationship between the tree growth and the precipitation in September and August of the current year as well as the September of the previous year. Notably, temperature was crucial, as there were significant positive relations found between the minimum and maximum temperatures and tree growth. The temperature of the previous year (September, November, and December) as well as the current year (June to November) had a positive correlation with the growth of tree rings. The results indicated that while temperature was favorable for chir pine radial growth practically all months and seasons, summer to post-monsoon precipitation limited tree growth. Furthermore, the increasing average minimum temperature had a more significant relation with the tree ring growth than the average maximum temperature. Our result demonstrated that the growth of subtropicalP. roxburghiiresponded positively to the present scenario of rising temperature and falling precipitation in the study area. This research contributes valuable insights into the complex dynamics of forest ecosystems and their responses to changing environmental conditions.
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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".