Interactive effects of carbon dioxide concentration and light on the morphological and biomass characteristics of black spruce and white spruce seedlings
Bibliographic record
Abstract
CO2–light interactions can influence the competition among boreal plants, but are poorly understood. We investigated the effect of such interactions on the growth and biomass of 1-year-old black spruce (Sb) ( Picea mariana (Mill.) BSP) and white spruce (Sw) ( Picea glauca (Moench) Voss) grown with CO2 concentrations ([CO2]) of 360 and 720 µmol·mol–1 under 30%, 50%, and 100% light, in greenhouses. There were significant two-way and three-way interactions. Root collar diameter (RCD) of Sw decreased with decreasing light, while in Sb, there was no significant difference in RCD for plants grown under 50% or 30% light. Height was greater for plants grown under 100% light than if the plants were shaded. Elevated [CO2] increased RCD by 33% and enhanced stem volume by 67%, 98%, and 84% under 100%, 50%, and 30% light, respectively. The CO2 enhancement of total biomass was relatively higher under lower light, and greater for Sb than Sw. Elevated [CO2] decreased specific leaf area under 50% light only. Root mass was generally higher under 100% light than when shaded. Elevated [CO2] increased the root mass of Sb under 100% light, but decreased it under 30% light. Elevated [CO2] decreased the shoot/root ratio under 100% light, but increased it under 30% light. Our data suggest that raising [CO2] will likely increase species competitiveness under low light conditions, and that the increase will be greater in species that are relatively shade tolerant.
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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) | 0.001 | 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".