A millennium-long perspective on high-elevation pine recruitment in the Spanish central Pyrenees
Bibliographic record
Abstract
Long-term fluctuations in forest recruitment, at time scales well beyond the life-span of individual trees, can be related to climate changes. The underlying climatic drivers are, however, often understudied. Here, we present the recruitment history of a high-elevation mountain pine (Pinus uncinata Ram.) forest in the Spanish central Pyrenees throughout the last millennium. A total of 1108 ring-width series translated into a continuous chronology from 924 to 2014 CE, which allowed estimated germination dates of 470 trees to be compared against decadal-scale temperature variability. High recruitment intensity mainly coincided with relatively warm periods in the early 14th, 15th, 19th, and 20th centuries, whereas cold phases during the mid-17th, early 18th, and mid-19th centuries overlapped with generally low recruitment rates. In revealing the importance of prolonged warm conditions for high-elevation pine recruitment in the Pyrenees, this study suggests increased densification and even possible upward migration of tree-line ecotones under predicted global warming.
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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 | 0.002 | 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) | 0.001 | 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 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".