Co<sub>2</sub>and O<sub>3</sub>Effects on Paper Birch (Betulaceae:<i>Betula papyrifera</i>) Phytochemistry and Whitemarked Tussock Moth (Lymantriidae:<i>Orgyia leucostigma</i>) Performance
Bibliographic record
Abstract
Elevated atmospheric concentrations of CO2 and O3 are known to alter the chemical composition of foliage, which in turn may affect the performance of herbivorous insects. We investigated the independent and interactive effects of CO2 and O3 on foliar quality of paper birch (Betula papyrifera Marshall) and the consequences of chemical changes for performance of the whitemarked tussock moth Orgyia leucostigma (J. E. Smith). The experimental design was a 2 by 2 factorial, with ambient and elevated levels of CO2 and O3, respectively. Foliage was analyzed for concentrations of nitrogen, starch, and condensed tannins. CO2 and O3 independently and interactively affected nitrogen concentrations, with the elevated CO2 + O3 treatment reducing nitrogen concentrations more than either treatment alone. Elevated CO2 and O3 had no significant effect on starch and tannin concentrations when administered alone but increased starch concentrations by 17% over ambient when administered together. Larvae were reared on experimental trees from egg hatch through pupation to determine treatment effects on development time and pupal mass. Larval performance measures were not statistically different among fumigation treatments, although females tended to have reduced pupal mass under the elevated CO2 + O3 treatment. These results demonstrate that chemical responses of some plant species to elevated levels of CO2 (560 μl L−1) and O3 (1.5 × ambient) may be of insufficient magnitude to significantly alter standard measures of individual insect performance.
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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 | 0.001 |
| 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".