Climate relationships of growth and establishment across the altitudinal range of Fagus sylvatica in the Montseny Mountains, northeast Spain
Bibliographic record
Abstract
A rise in elevation of the temperate biome has been reported in the mountains of northeast Spain. We aimed to determine the principal climatic factors limiting growth and establishment of the dominant temperate tree, Fagus sylvatica, across its altitudinal range and how its climate-response has varied over time. We determined the climate-response of the growth of adult trees and the establishment of juveniles using dendroecological methods at 3 sites along an elevational gradient spanning this species' full altitudinal distribution of approximately 1000–1650 m above sea level. We found strong altitudinal variation in growth and establishment responses to climate. The most common growth response was to high spring and summer temperature (April–July), which promoted growth and establishment at the upper treeline but had the opposite effect at low altitudes. Precipitation was strongly limiting for adult growth at the lower limit of F. sylvatica and declined in importance with increasing altitude. Sensitivity of growth to summer temperature increased over the second half of the 20th century. Future increases in summer temperature are likely to have negative consequences for growth and establishment at this species' low altitude, low latitude range-edge, particularly if temperature increase is not matched by increasing precipitation.
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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 | 0.001 |
| 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".