Phenotypic plasticity enables considerable acclimation to heat and drought in a cold-adapted boreal forest tree species
Bibliographic record
Abstract
Increasing frequencies of severe heat waves and drought are expected to influence the composition and functioning of ecosystems globally. Our ability to predict and mitigate these impacts depends on our understanding of species- and age-specific responses to these stressors. To assess the adaptive capacity of balsam fir to climate change, a cold-adapted boreal tree species, we conducted a climate-controlled greenhouse experiment with four provenances originating from across the species biogeographic range, 12 temperature treatments ensuring a minimum of +11°C warming, and five drought treatment intensities. We found considerable acclimation to temperature and drought treatments across all provenances, with steady gains in biomass under temperatures well-beyond the “worst-case” (RCP 8.5) climate forcing scenario within the species natural range. Acclimation was supported by high phenotypic plasticity in root:shoot ratio (RSR) and photosynthesis, which were greatly increased with warming, but were not affected by drought. Our results suggest that regardless of the observed provenance variation, drought and heat are not limiting factors of the current-year balsam fir seedling growth, instead, these factors may be more impactful on later stages of regeneration or previously stressed individuals, thus highlighting the necessity of incorporating the factors of ontogeny and provenance origin in future research regarding plant and climate interactions.
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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".