Genotypic variation in growth of Picea glauca (Moench (Voss)) to elevated carbon dioxide
Bibliographic record
Abstract
Atmospheric CO₂ levels are rising, and anticipated to double before the end of this century. Elevated CO₂ affects many aspects of plant function, and these effects vary both inter- and intra-specifically. However, the magnitude of intra-specific variation in woody plants has not been well documented, and the mechanistic basis for this variation is largely unexplored. This study examined intra-specific variation in response to elevated carbon dioxide in twenty-nine genotypes of white spruce (Picea glauca), a widely distributed and economically important conifer species in Canada. Trees were exposed to ambient CQ₂ levels (370ppm) or twice-ambient CO₂ levels (740ppm). Regular measurements of tree height and diameter were taken, in addition to transpiration and biomass measurements at the end of the experiment. All genotypes exhibited an increase in biomass in the elevated CO₂ treatment; however, considerable variation was observed in the degree of response among genotypes. Depending on the genotype, biomass enhancement under the HC treatment ranged from 18.8% to 96.7% with a mean of 51.7%. Genotypes exhibiting a large response to elevated CO₂ tended to allocate more fixed carbon towards growth in height and less towards increase in stem diameter. These genotypes also tended to have the highest growth rates, regardless of the level of CO₂.
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 | 0.000 | 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) | 0.000 | 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".