Use of tree rings to study the effect of climate change on trembling aspen in Québec
Bibliographic record
Abstract
Abstract In this paper, we present a new approach, based on a mixed model procedure, to quantify the tree‐ring‐based growth‐climate relationship of trembling aspen along a latitudinal gradient from 46 to 54 °N in eastern Canada. This approach allows breaking down the growth response into general intersite and local climatic responses, and analyzing variations of absolute ring width as well as interannual variations in tree growth. The final model also integrates nonclimatic variables such as soil characteristics and the occurrence of insect outbreaks into the growth predictions. Tree level random effects on growth were important as intercepts but were nonsignificant for the climatic variables, indicating that a single climate–growth relationship was justified in our case. The response of tree growth to climate showed, however, a strong dependence on the spatial scale at which the analysis was performed. Intersite variations in tree growth were mostly dependent on variations in the thermal heat sum, a variable that showed low interannual and high intersite variation. When variation for a single site was analyzed, other variables showed up to be important while the heat sum was unimportant. Finally, future growth under six different climate change scenarios was simulated in order to study the potential impact of climate change. Results suggest only moderate growth increases in the northern portion of the gradient and a growth decrease in the southern portion under future climatic conditions.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".