Why do genotypes of Picea glauca differ in their growth response to elevated CO2?
Bibliographic record
Abstract
Meta-analyses reveal that fast-growing species have a greater growth response to elevated CO(2) than slow-growing species. It is unknown whether this is a direct response or whether inter-specific differences in growth are simply correlated with other physiological or morphological differences among species that affect the growth response to CO(2). Here we use intra-specific variation in Picea glauca to examine the mechanistic basis for this relationship. Relative growth rate (RGR) of 29 genotypes grown at ambient (370 µl l(-1)) or elevated (740 µl 1(-1)) CO(2) was measured. Physiological and morphological traits describing differences in allocation, canopy structure, stomatal function and photosynthesis were determined. Most variation in RGR (74%) was explained by traits associated with canopy structure. Although there was a strong correlation between RGR(740) and RGR(370), we found no evidence that genotypes that grew fast at ambient CO(2) had a greater relative growth response to CO(2). Given that the pattern found at the intra-specific level differed from that reported at the inter-specific level, our results suggest that RGR per se does not affect the growth response to CO(2). Rather, the CO(2) growth response is determined by traits that may or may not be correlated with RGR.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".