Reassessment of growth-climate relations indicates the potential for decline across Eurasian boreal larch forests
Bibliographic record
Abstract
Larch, a widely distributed tree in boreal Eurasia, is experiencing rapid warming across much of its distribution. A comprehensive assessment of growth on warming is needed to comprehend the potential impact of climate change. Most studies, relying on rigid calendar-based temperature series, have detected monotonic responses at the margins of boreal Eurasia, but not across the region. Here, we developed a method for constructing temporally flexible and physiologically relevant temperature series to reassess growth-temperature relations of larch across boreal Eurasia. Our method appears more effective in assessing the impact of warming on growth than previous methods. Our approach indicates widespread and spatially heterogeneous growth-temperature responses that are driven by local climate. Models quantifying these results project that the negative responses of growth to temperature will spread northward and upward throughout this century. If true, the risks of warming to boreal Eurasia could be more widespread than conveyed from previous works.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| 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".