Contrasting Growth Response of Jack Pine and Trembling Aspen to Climate Warming in Quebec Mixedwoods Forests of Eastern Canada Since the Early Twentieth Century
Bibliographic record
Abstract
Abstract Forest monitoring studies show contrasting trends in tree growth rates since the mid‐twentieth century. However, due to their focus on annual and decadal dynamics, they provide limited insight into the effects of long‐term climatic variability on tree growth. Here, we relied on a large tree‐ring dataset (∼2,700 trees) of two common North American shade‐intolerant tree species, trembling aspen (Populus tremuloides Michx.) and jack pine (Pinus banksiana Lambert), to assess their lifespan‐long growth dynamics in the mixedwood forests of Québec. We also determined how the environmental conditions of the stands influenced tree growth. We observed a significant increase in the radial growth rate of trembling aspen during the study period, while the jack pine decline was not significant. Over the whole study region, the trees growing in sites with lower competition, and those at the lower sections of the terrain slope experienced more of the positive effects of temperature on growth rates. Our study suggests that the tree growth response to climate warming may be species‐specific and will vary across the boreal mixedwoods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".