Climate change experiment suggests divergent responses of tree seedlings in eastern North America’s Acadian Forest Region over the 21st century
Bibliographic record
Abstract
In this study, we conducted a controlled experiment to assess the growth and survival of balsam fir (Abies balsamea (L.) Mill.), red spruce (Picea rubens Sarg.), and red maple (Acer rubrum L.) seedlings in response to warming, drought, and elevated CO2, as projected under RCP 8.5 for North America’s Acadian Forest Region. In response to warming, only red spruce increased in height; however, this effect varied by CO2 and soil moisture treatments. Under the drought treatment, red spruce biomass was not affected, but mortality increased by 2%. With warming, increases in balsam fir height growth were only detected under certain soil moisture and CO2 conditions. Balsam fir biomass decreased by 24% under drought, while mortality increased by 5%. Warming did not improve red maple height growth, but it remained 7–50 times greater than that of the conifers and no mortality was observed. Overall, CO2 enrichment increased height growth of droughted seedlings relative to the ambient treatment, demonstrating an amelioration of the negative drought effect. Balsam fir was the least adapted to warming and drought, while red spruce displayed some positive responses. Although growth of red maple seedlings did not increase with warming, they exhibited greater absolute growth and survival, which suggests red maple may outperform both conifers under a warming climate.
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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 | 0.000 |
| 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 | 0.000 | 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".