Coupled, decoupled, and abrupt responses of vegetation to climate across timescales
Bibliographic record
Abstract
Climate and ecosystem dynamics vary across timescales, but research into climate-driven vegetation dynamics usually focuses on singular timescales. We developed a spectral analysis–based approach that provides detailed estimates of the timescales at which vegetation tracks climate change, from 10 1 to 10 5 years. We report dynamic similarity of vegetation and climate even at centennial frequencies (149 −1 to 18,012 −1 year −1 , that is, one cycle per 149 to 18,012 years). A breakpoint in vegetation turnover (797 −1 year −1 ) matches a breakpoint between stochastic and autocorrelated climate processes, suggesting that ecological dynamics are governed by climate across these frequencies. Heightened vegetation turnover at millennial frequencies (4650 −1 year −1 ) highlights the risk of abrupt responses to climate change, whereas vegetation-climate decoupling at frequencies >149 −1 year −1 may indicate long-lasting consequences of anthropogenic climate change for ecosystem function and biodiversity.
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".