Common tree growth anomalies over the northeastern Tibetan Plateau during the last six centuries: implications for regional moisture change
Bibliographic record
Abstract
Abstract The world's hydrological cycle is believed to intensify with global warming, yet current climate models have only a limited ability to assess moisture responses at regional scales. Tree‐ring records are a valuable source of information for understanding long‐term, regional‐scale moisture changes, particularly for large regions such as the Tibetan Plateau (TP), where the observational data are short and sparse. Here, we present a new ring‐width chronology developed from Qilian Juniper (Sabina przewalskii) wood at two sites on the northeastern TP. This chronology, combined with others from the same region, demonstrates that tree growth anomalies are linked to regional late spring to early summer moisture availability. Although late monsoon season precipitation in the study area decreased during recent decades, tree growth continued to increase due to persistent moisture availability in the early monsoon season. Comparison with global sea surface temperatures (SSTs) indicates that early (late) monsoon season precipitation is closely related to tropical Pacific (Indian Ocean) SSTs, suggesting a possible seasonal shift in the dominant moisture source area for monsoonal precipitation over the northeastern TP. It is further shown that there is a very high degree of coherency regarding low‐frequency tree growth anomalies over the northeastern TP during the last six centuries. The most prominent drought epoch occurred during ca. 1450–1500, which may have been caused by a significant decrease in the thermal gradient between the Eurasian continent and the tropical oceans. A persistent tree growth increase since the 1880s is coincident with global warming, suggesting an intensified early monsoon season moisture regime in the study area.
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 | 0.000 | 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 | 0.000 | 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".