Testing for tree‐ring divergence in the European Alps
Bibliographic record
Abstract
Abstract Evidence for reduced sensitivity of tree growth to temperature has been reported from multiple forests along the high northern latitudes. This alleged circumpolar phenomenon described the apparent inability of temperature‐sensitive tree‐ring width and density chronologies to parallel increasing instrumental temperature measurements since the mid‐20th century. In addition to such low‐frequency trend offset, the inability of formerly temperature‐sensitive tree growth to reflect high‐frequency temperature signals in a warming world is indicated at some boreal sites, mainly in Alaska, the Yukon and Siberia. Here, we refer to both of these findings as the ‘divergence problem’ (DP), with their causes and scale being debated. If DP is widespread and the result of climatic forcing, the overall reliability of tree‐ring‐based temperature reconstructions should be questioned. Testing for DP benefits from well‐replicated tree‐ring and instrumental data spanning from the 19th to the 21st century. Here, we present a network of 124 larch and spruce sites across the European Alpine arc. Tree‐ring width chronologies from 40 larch and 24 spruce sites were selected based on their correlation with early (1864–1933) instrumental temperatures to assess their ability of tracking recent (1934–2003) temperature variations. After the tree‐ring series of both species were detrended in a manner that allows low‐frequency variations to be preserved and scaled against summer temperatures, no unusual late 20th century DP is found. Independent tree‐ring width and density evidence for unprecedented late 20th century temperatures with respect to the past millennium further reinforces our results.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".