Data from: Climatic change only stimulated growth for trees under weak competition in central boreal forests
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
1. Global change ecologists have often used trees under weak competition (e.g., dominant/codominant trees) to examine relationships between climatic change and tree growth. Scaling up these results to a forest relies on the assumption that the climatic change-tree growth relationship is not affected by tree-level competition. 2. Using permanent sample plot data from the central Canadian boreal region where warming did not result in water deficit, we tested the above-mentioned assumption by looking at whether the relationship between climatic change and tree growth varied with tree-level competition, which was quantified using a modified Hegyi competition index. 3. We found that tree growth increased over time for trees under weak competition, but decreased for those under strong competition. The divergent temporal trends among trees under different levels of competition led to a non-significant change in growth for our study plots. Growth increased with regional warming, atmospheric [CO2] and water availability for trees under weak competition, but not for those under strong competition. 4. Synthesis. Our results suggest that upscaling the growth responses of dominant/codominant trees to climate change to a forest or a region can lead to biased estimates. Tree-level competition should be taken into account when expressing climatic change and tree growth relationships.
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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 | 0.001 | 0.000 |
| 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 | 0.002 | 0.017 |
| Open science | 0.008 | 0.004 |
| 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 it