Seasonal shift in the climate responses of<i>Pinus sibirica</i>,<i>Pinus sylvestris</i>, and<i>Larix sibirica</i>trees from semi-arid, north-central Mongolia
Bibliographic record
Abstract
In light of a significant increase in the warming trend observed in recent decades in semi-arid Mongolia, tree-ring attributes and anomalies were analysed to detect potential changes in the growth–climate relationship. In a moisture-limited environment, an increase in temperature could cause a shift in the seasonal response of trees to climate. Chronologies were developed for the dominant tree species (Larix sibirica Ledeb., Pinus sibirica Du Tour, and Pinus sylvestris L.) from north-central Mongolia. In addition to annual ring width, both earlywood and latewood width were measured, and tree-ring anomalies such as false rings and light rings were systematically identified. Earlywood width was mainly associated with precipitation in the year prior to ring formation and early growing season conditions. Temperature was associated with current year growth and mainly influenced latewood development. False rings were good indicators of early summer droughts, whereas light rings were mainly associated with a cold end of summer. A seasonal shift in the significance of monthly climate variables was observed in recent decades. This displacement presumably resulted from changes in the timing and duration of the growing season. Tree growth starts earlier in spring and is now affected by late summer to early autumn climate conditions.
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 | 0.000 |
| 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) | 0.000 | 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 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".