Reducing continuous synchrony is an inherent property of tree growth in forests
Bibliographic record
Abstract
Abstract Forests play an important role in providing ecosystem services and regulating carbon balance. Modelers rely on the implicit assumption that, under the common climate drivers, trees have similar growth patterns over large spatial scale. Using ring-width sequences of 1046 juniper trees from Tibetan Plateau and 538 pine trees in the eastern China, we show that, although tree growth is influenced by climatic factors, individual trees often do not respond in a synchronous manner. After highly synchronous growth events, the number of trees exhibiting common growth change declined progressively and, notably, the patterns of decline exhibited the form of exponential function with parameter of base b ranging from 0.57-0.83 for juniper forests in Tibetan Plateau and from 0.56-0.72 for pine forests in eastern China. Our findings suggest that individual trees in forests tend to grow independently with respect to climate rather than synchronously, and that a relatively uniform pattern of growth de-synchronization is an inherent property of forest tree growth. We propose that this property is essential for trees collectively to have resilience and maintain forest stability, analogous to maintaining a diverse investment portfolio as a strategy to cope with unexpected risks. This new perspective on widespread non-synchronous radial tree growth sheds insight into fundamental ecological processes in forest resilience and can improve assessment and management of forest health risks under future climate change.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| 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 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".