Contrasting acclimation abilities of two dominant boreal conifers to elevated CO<sub>2</sub> and temperature
Bibliographic record
Abstract
Abstract High latitude forests will experience large changes in temperature and CO2 concentrations this century. We evaluated the effects of future climate conditions on 2 dominant boreal tree species, Pinus sylvestris L. and Picea abies (L.) H. Karst, exposing seedlings to 3 seasons of ambient (430 ppm) or elevated CO2 (750 ppm) and ambient temperatures, a + 4 °C warming or a + 8 °C warming. Pinus sylvestris responded positively to warming: seedlings developed a larger canopy, maintained high net CO2 assimilation rates (Anet), and acclimated dark respiration (Rdark). In contrast, carbon fluxes in Picea abies were negatively impacted by warming: maximum rates of Anet decreased, electron transport was redirected to alternative electron acceptors, and thermal acclimation of Rdark was weak. Elevated CO2 tended to exacerbate these effects in warm‐grown Picea abies, and by the end of the experiment Picea abies from the +8 °C, high CO2 treatment produced fewer buds than they had 3 years earlier. Treatments had little effect on leaf and wood anatomy. Our results highlight that species within the same plant functional type may show opposite responses to warming and imply that Picea abies may be particularly vulnerable to warming due to low plasticity in photosynthetic and respiratory metabolism.
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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".